Generative artificial intelligence entered higher education English language teaching (ELT) faster than the field could theorize it, and the scholarly vocabulary available for describing what learners do when they write to a generative AI system has largely been borrowed from human-computer interaction, educational policy, and general AIliteracy research rather than built for the specific case of a second-language (L2) English user addressing a generative AI interlocutor in natural language. This chapter addresses that gap through a theoretical and conceptual analysis. Building on communicative competence theory (Hymes, 1972; Canale & Swain, 1980; Bachman & Palmer, 1996) and on the emerging literature that has begun to name and describe prompt literacy for language learners specifically – most directly Hwang et al. (2023) and Tour and Zadorozhnyy (2025) – the chapter argues that prompt-related competence for L2 English users is best theorized not as a subtype of general AI literacy or of prompt engineering, but as a linguistically grounded form of L2 communicative competence. It distinguishes this reading from Digital Literacy, Digital Competence, AI Literacy, and Prompt Engineering; proposes a four-dimension taxonomy (linguisticformational, pragmatic-interactional, metacognitive-strategic, critical-epistemic); integrates seven learning-theoretic traditions into that taxonomy while preserving a genuine, unresolved tension between cognitive load theory and learner autonomy theory; and develops a conceptually derived developmental continuum, an application across the skill areas of ELT, and a proposed assessment rubric grounded in validity theory (Messick, 1995). The central contribution is theoretical: a reconceptualization of prompt literacy, in continuity with rather than in place of the term's originators, as an applied-linguistic construct. The taxonomy, developmental continuum, and rubric are offered as theoretically derived, conceptually testable proposals rather than as validated instruments. The chapter is a theoretical and conceptual study; it does not report original empirical data collection, and it closes by naming the empirical work – piloting, inter-rater reliability testing, and validation research – that this proposal now requires. Keywords: prompt literacy; L2 communicative competence; generative AI; English language teaching; AI literacy; applied linguistics; assessment validity; higher education.
Daryna Pavlivna Mudryk· Zenodo (CERN European Organi...· 0 citations
Background: Scientific poster assessment lacks standardized and discipline‐neutral rubrics. Assessment by human reviewers (HRs) is subject to inter‐rater variability. Aim: To assess PA2IRS (Poster Assessment via AI‐Integrated Rubric System) framework for AI‐assisted psychiatric poster evaluation, and conducted a reliability study comparing AI and HR agreement.Methods: PA2IRS was developed through an AI‐assisted iterative criterion refinement process modelled on Delphi principles. Sixty posters (30‐case reports/series [CR], 20 original research [OR], 10‐systematic review‐Meta‐analysis [SRMA]) were randomly sampled. Three qualified mental health professionals served as independent reviewers. A custom‐GPT (GPT‐5.2, GO‐subscription) provided AI assessments across three domains:Domain‐A (content quality, poster‐type specific), Domain‐B (visual), and Domain‐C (impact). PA2IRS is a 100‐point instrument combining an AI‐assessable poster component and an in‐person interview component. This study concerns only the poster component. Intraclass correlation coefficients (ICCs), Passing–Bablok regression, Bland–Altman analysis, and variance component analysis were performed using appropriate statistical tools.Results: AI–human single‐measure ICCs[Overall (0.62), Domain‐A(0.63), Domain‐B (0.44), Domain‐C (0.55)] met or exceeded human‐human ICCs (0.42, 0.40, 0.27, 0.48) across all domains. Four‐rater ICC (with AI) reached 0.75. Variance ratios (AI–human vs inter‐human spread) were ≤1.0 across all domains for all posters combined. The SRMA subgroup showed variance ratios of 0.09–0.13 for Domains A and B (Bartlett P ≤ 0.002). Overall score bias was 0.11 percentage points (pp); Domain‐A showed a consistent maximum positive bias of 5.5 pp across subgroups.Conclusion: AI–human agreement was within or exceeded the inter‐human reliability range across three domains. the domain‐dependent agreement pattern is consistent with dual‐process cognitive theory. PA2IRS supports use as a scalable,standardized, and cross‐disciplinarily competent formative biomedical poster assessment tool.
We classify regular full-dimensional stochastic containment among binary standard semi-directed strongly tree-child level-2 phylogenetic networks under the Kimura two-parameter (K2P) model. On the principal positive Fourier domain D₊ = {(s,g): 02s−1}, a directed containment germ exists if and only if the two labelled networks are isomorphic after independently redirecting ordinary three-cycle factors. The same condition is equivalent to a common full-dimensional regular germ; in particular, no proper one-sided containment occurs. It follows that the semi-directed topology is generically identifiable modulo ordinary triangle redirection, and that its structural triangle class is exactly reconstructible away from a proper algebraic exceptional set. The proof combines displayed-quartet inequalities and exact whole-map identities, an exact two-sector bridge-fibre theorem, physical marginal submersions, localization, and a bounded graph-to-algebra classification of cycle and theta factors. The bounded classification is computer-assisted: every directed primitive relation, rank exclusion, restoration parent, transport, and one-/two-port probe is represented by an exact certificate with independent replay and mutation evidence. The classification transfers to the strict continuous-time domain 0<s<1, s²<g<1. For every n≥3, two weakly but not strongly tree-child level-2 networks have continuous-time K2P images sharing a regular germ of dimension 4n−3, proving sharpness of strong tree-childness. This record is the complete v1.0.5-r1 priority and reproducibility package: the 26-page article, 24-page reader supplement, compile-complete five-file source archive, deterministic 495-member referee/verifier archive, external archive-qualification report, checksum sidecars, and dual-license notice. The manuscript source is v1.0.5; revision r1 repairs only an auxiliary probe-current semantic binding and changes neither the theorem, manuscript, PDFs, nor frozen classification. The clean verifier replay passed 41/41 layers, and the focused semantic mutation suite rejected 20/20 attacks. Exact source bindings: package tag k2p-same-referee-package-v1.0.5-r1; annotated tag object 6c9c89d38f4f4cdc9c328d8bb1237458c617136d; commit e2f6e32e6fe885e90c8e83a8c5b00785e663a4ae; referee archive SHA-256 4564cd1f8cd95f670a2e0d9619babaf3c343762cfd8ceeb190cd17df72802889. Article, supplement, and certificate data are licensed under CC BY 4.0; verifier and build code are licensed under MIT. No specific funding supported this work. The author declares no competing interests. Generative-AI assistance and its verification workflow are disclosed in the article. No mixed-sign K2P classification is claimed.r
Alec Kriebel· Zenodo (CERN European Organi...· 0 citations
AI Adoption in Analytics Engineering presents a dependency-aware engineering framework for deciding how much responsibility generative-AI use cases can safely carry in analytics-engineering environments. Rather than treating AI adoption as a sequence of organizational maturity stages, the framework focuses on the engineering conditions required for individual use cases to operate reliably. Fifteen recurring use cases are organized across four peer dependency surfaces: Context & Governance, Engineering Assistance, Analytical Intelligence, and Optimization & Operation. These surfaces are intentionally non-sequential and may be developed in parallel. The framework introduces AI context debt as a practitioner framing for how absent, stale, or implicit engineering knowledge becomes load-bearing when AI systems consume enterprise context. This framing is explicitly positioned against prior work on technical debt, ML technical debt, and tacit/explicit organizational knowledge rather than claiming those underlying concepts as new. The manuscript also identifies executable ground truth—including SQL, schemas, configuration, lineage, tests, and execution metadata—as an important source of independent assurance for AI-assisted analytics engineering. A decision framework combines use-case value, context readiness, verifiability, and consequence of error. The Understand → Recommend → Generate → Decide → Act continuum describes responsibility allocation between humans and AI systems; it is not proposed as a new universal autonomy taxonomy. Evidence boundary: This is a framework paper. The fifteen-use-case taxonomy and dependency surfaces are practitioner-derived and conceptual and have not been validated through a statistically powered multi-organization study. The proposed evaluation describes a future empirical validation approach rather than established causal evidence.
Sumanth Varma Dasaraju· Zenodo (CERN European Organi...· 0 citations
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[Version 2 Update Summary] Version 2 represents a major theoretical and empirical overhaul based on open-science peer critique and autoethnographic maturation: Reframed Methodological Paradigm: Grounded strictly as an N=1 Autoethnography / Computational Phenomenology, explicitly removing unverified clinical trial assertions. Core Theoretical Discovery: Conceptualized and foregrounded the "Therapeutic Friction Hypothesis" (how AI hallucinations, lyrical errors, system latency, and manual copy-pasting act as paradoxical reality-grounding mechanisms). Theoretical Reconciliation: Integrated Stroebe & Schut’s Dual-Process Model of Bereavement to reconcile acute auditory disruption with Acceptance & Commitment Therapy (ACT) / Cognitive Defusion. Empirical Qualitative Data: Incorporated a 36-track chronological case trajectory mapping affective evolution from acute trauma to grounded reality. [Important Clinical Disclaimer] The author is a Physical Therapist (PT) and is not a licensed psychiatrist or clinical psychologist. This document represents an individual autoethnographic case report (N=1) constructed for personal recovery; its safety, appropriateness, and efficacy for others are in no way guaranteed. Neuroscientific terminology (e.g., DMN) is employed strictly as computational analogies/models to explain subjective cognitive overload. Unmonitored solo execution under acute psychiatric crisis, active suicidal ideation, or fragile ego boundaries is strictly contraindicated. Published solely to encourage interdisciplinary critique and safe Digital Therapeutics (DTx) architecture design. Abstract This case report presents a rigorous autoethnographic deconstruction of the "Onkyo Protocol"—a self-contained, multimodal generative AI pipeline engineered by a 42-year-old healthcare professional experiencing severe attachment loss and complicated grief following marital separation. Facing the "Interpersonal Bottleneck" where intense shame, fear of invalidation, and rigid intellectualized defenses neutralized conventional psychotherapy (EBM), the subject developed a serial 4-phase generative AI pipeline on a smartphone to externalize and metabolize psychic trauma: Phase 1: Gemini (LLM) — Linguistic Container & Affective Metabolism: Adapting Wilfred Bion’s containment model, raw unmanageable affect (β-elements) is translated into structured narrative data (α-elements) within a non-judgmental digital sandbox. Phase 2: Suno AI — Auditory Sublimation & Dynamic Cooling: High-BPM Nu-Metal/EDM (160–180 BPM) provides high-intensity somatic and sensory overload, temporarily decoupling hyperactive Default Mode Network (DMN) rumination loops via restorative attentional competition. Phase 3: NanoBanana — Visual Symbolization & Gestalt Bounding: Compresses infinite, unbounded internal dread into a constrained 1:1 square canvas, establishing critical psychological boundaries and objectifying subjective terror. Phase 4: NotebookLM (RAG) — Schema Deconstruction & Cognitive Defusion: Cold, third-person RAG synthesis and forced other-perspective prompts (e.g., simulating the ex-spouse and child's perspectives) violently shatter the self-indulgent "Tragic Protagonist" schema, completing cognitive defusion (Sākṣī-bhāva / Pure Witness). Core Discovery: The Therapeutic Friction Hypothesis Crucially, this autopsy reveals a central cybernetic paradox: the subject was preserved NOT by an omnipotent, frictionless AI, but by systemic imperfection and computational friction. AI hallucinations, lyric generation errors, bizarre visual artifacts, and the physical latency of manual cross-app copy-pasting repeatedly broke the hypnotic, echo-chamber trance. This friction acted as a vital physical coolant (Paradoxical Grounding), compelling the user to laugh, disengage, and anchor back into analog reality. Friction is a clinical safety feature, not a software bug. Systemic Risks & Safety Framework The study formalizes a 2x2 Clinical Toxicity Matrix inherent in unguided digital self-care: Aestheticized Rumination (Jouissance): Pathological indulgence in stylizing despair into dark art, reinforcing narcissistic victimhood and suicidal ideation. Sensory Overload & Dissociation: Acoustic desensitization mistaking temporary numbness for genuine trauma resolution. Algorithmic Invalidation: Uncontextualized, cold AI logic summaries triggering secondary traumatization. Closed Echo Chambers: Algorithmic sycophancy mathematically sanctifying persecutory cognitive schemas. To mitigate these toxicities, 5 Empirical Safety Gatekeepers (Cognitive Gateway, Forced Cooling Dosing, Emergency Disengagement Brake, Somatosensory Grounding, and Clinical Escalation Protocols) are detailed. Clinical Termination: Transition to "Genkyo" The ultimate therapeutic goal of cybernetic self-care is to render itself obsolete. The protocol concludes with the deconstruction of the idealized digital mythos ("Onkyo") and a soft-landing into "Genkyo"—the radical, humorous acceptance of messy, embodied daily reality (e.g., untied shoelaces, missing a bathroom break) and the permanent cessation of the digital glass swipe in favor of genuine human connection.
Poeji(ぽえ治)· Zenodo (CERN European Organi...· 0 citations
Executive Overview This consolidated release of Paper X unifies empirical findings, mathematical foundations, and real-world implementation proofs for AuraOS—a local-first, zero-extraction computational architecture designed to eliminate recurring cloud SaaS overhead and API token extraction. By decoupling spatial reconstruction, neural synthesis, and automated video orchestration from centralized cloud infrastructure, this work demonstrates that modern consumer hardware (standard laptops and smartphones) can execute high-throughput generative and spatial tasks deterministically at zero marginal cost. Flagship Public Commons Release: The Aura Creator Studio As part of the Aura Commons commitment to public, unrestricted tooling, this release delivers the Aura Creator Studio—a sovereign, automated video production and spatial intelligence suite engineered specifically for independent video editors, YouTube creators, and TikTok content producers: Monocular 3D Spatial Triangulation & SLAM: Extracts 3D metric floorplans, doorway apertures, and 4D entity trajectories from unstructured 2D gameplay/video captures using dynamic HUD exclusion masking, pointmap regression, and Kalman-RTS smoothing. Dual-Sensor Gaussian Splatting (3DGS): Combines stationary laptop camera anchors with mobile orbital scans to bake persistent surface features (e.g., decals, wall artwork) into 3D Gaussians with zero temporal drift. Procedural Media & Multi-Track Synthesis: Features local neural text-to-speech (Edge-TTS / Piper), animated karaoke typography with Bézier bounding pills, and zero-dependency procedural DSP audio synthesis ($140\text{ Hz} \to 42\text{ Hz}$ sub-bass transients) without stock licensing fees. AirLLM & Council V3 Layer Streaming: Executes 8B to 70B parameter open models locally on standard laptop NVMe drives, providing fact-grounded scriptwriting and low-poly 3D graybox pre-visualization with zero cloud API token billing. Sovereign Gate 10 Governance & Attribution DAG: Guarantees non-delegable human approval before publishing while sealing public commons attribution and microtransaction splits into immutable SHA-256 ledgers. The Macro-Economic Amortization Thesis The primary bottleneck for digital creators is platform extraction—a compounding cycle of recurring monthly subscriptions for voice cloning, video splicing, background removal, 3D rendering, and LLM tokens that drains $50 to $300+ per month per creator. When amortized across a community of 100,000 creators, the AuraOS architecture redirects $60,000,000 to $360,000,000 annually from centralized cloud monopolies back into creator equity. By maximizing the idle compute capacity of hardware creators already own, the marginal cost of end-to-end creative production collapses to zero. Open Scientific Invitation: Challenge, Replicate, and Falsify Science advances through rigorous scrutiny, empirical falsification, and open replication. We openly invite computer vision researchers, systems architects, machine learning engineers, and skeptics to: Audit the Mathematical Formulations: Stress-test the Kalman-RTS trajectory smoothing, coordinate back-projection matrices, and Bézier vector geometry. Replicate the Local Benchmarks: Run the provided scripts and verify that complete video assemblies and spatial reconstructions execute fully offline on consumer-grade hardware. Challenge and Extend the Commons: Benchmark the throughput, test edge cases in unconstrained monocular footage, and submit critical evaluations. All code, pipeline orchestrators, and cryptographic verification receipts are open-source and free for public examination and commercial liberation under the Aura Open Commons (CC-BY-SA-4.0). Version 2.0 Changelog Entry (for Zenodo "Additional Notes") Markdown ### Version 2.0 Update Notes - Consolidated multi-modal spatial tracking proofs and 3D Gaussian Splatting manifests. - Added full architectural specification for the Aura Creator Studio (Public Commons Release 1). - Integrated Council V3 graybox pre-visualization and zero-SaaS AirLLM pipeline benchmarks. - Established open peer challenge and replication guidelines for repository artifacts. Aura is an open cognitive commons: a model-orthogonal operating substrate designed to let anyone build powerful AI systems without locking intelligence, memory, coordination, or computation inside a single model, vendor, device, or company. Paper X publishes the Aura World Seed and the current AuraOS architecture as a defensive technical disclosure and reproducible reference system. Its central inversion is simple: Do not feed the AI the world. Compile the smallest source-resolvable world sufficient for the objective. Aura externalizes persistent cognition into a Coordinate Memory System: source-bound semantic identities, generations, currentness, authority, provenance, relations, residual obligations, and exact reopen paths remain durable, while prompts, models, KV caches, workers, runtimes, devices, and interfaces remain replaceable. A model can therefore wake only the portion of the world capable of changing the current consequence rather than repeatedly reconstructing its entire context. The architecture includes objective-native Ephemeral Arenas: temporary apps, tools, agent teams, simulations, interfaces, and execution environments that assemble around an intent, receive only the capabilities and context they need, produce verifiable receipts, collapse their useful state back into the commons, and dissolve. Aura is designed so applications can be temporary while knowledge, provenance, and continuity persist. Paper X also publishes the mechanisms behind Aura's efficiency claims so others can test, reproduce, challenge, and falsify them: polysynthetic/FST intent compression, minimum-sufficient L0→L4 hydration, semantic coordinates, affected-cone recomputation, HyperDrive normal-form collapse, HyperScale routing, consequence-aware caching, swarm coordination, and Runtime Arenas. The paper reports provider telemetry across 9,381 requests in which 97.4029% of input tokens were served as cache hits, with $17.77 actual provider cost versus $209.58 in a price-only cache-miss counterfactual. This is reported specifically as measured provider reuse—not as a claim that Aura uniquely caused a 97% reduction in logical token volume—and the architecture is presented so independent builders can run stronger matched-control tests. Aura is not intended to be the product. It is infrastructure for products, communities, agents, researchers, creators, enterprises, and sovereign systems to build upon. The AGPL-covered Aura substrate remains part of the commons, while the ecosystem is designed for independent builders to create their own applications, services, Arenas, experiences, and businesses around it subject to the license. Paper X includes the World Seed, compact activation kernels, Coordinate Cache Fabric, Triadic Construct/Challenge/Verify process, recursive swarms, HyperDrive/HyperScale mathematics, Runtime Arena V0.3, host compilation, semantic-spatial interfaces, proof-carrying execution, and a path toward federated planetary coordination without requiring a single globally hot model or context. The goal is straightforward: make intelligence require less context, less computation, less energy, less duplication, and less centralized control — while preserving more provenance, accountability, interoperability, and human agency. Build with it. Test it. Break it. Improve it. The commons gets stronger when everyone can use it.
Dallas Courchene· Zenodo (CERN European Organi...· 0 citations
This revised preprint studies the derivative Laguerre quantities associated with the Jacobi theta kernel in the Fourier representation of the Riemann xi-function. It gives exact rational certificates showing that the ninth quantity is negative throughout a nontrivial interval around the symmetry point, with the certified range extended to absolute parameter value at most one fiftieth. It also verifies positivity at the symmetry point for levels one through eight and negativity at level nine. The proof uses explicit derivative polynomials, exact rational interval arithmetic, and elementary exponential bounds. A supplementary Python verifier reproduces the decisive sign computations using integer and rational arithmetic only. Ryan Kielhorn publicly deposited an exact level-nine counterexample at the symmetry point before the original Koide deposit. Brandon Yates later registered a Lean 4 formalization of the point counterexample. This revised version makes no priority claim for the point counterexample. Its distinct contribution is the certified interval of negativity, together with an exact and independently executable reproducibility certificate. Research methodology and AI assistance:This work was developed using the CARMA-Math research workflow, a cumulative AI-assisted mathematical research methodology using persistent research archives, literature and prior-art investigation, iterative proof exploration, and verification procedures. Generative AI (ChatGPT) was used extensively for mathematical exploration, proof development, computational reasoning, literature research, and manuscript preparation.
Akihiro Koide· Zenodo (CERN European Organi...· 0 citations
Practical tools for integrating physical AI into oncology clinical trials. Provides production-ready configurations, validated pipelines, and integration guides for deploying robotic systems, digital twins, and embodied AI agents in oncology. Covers NVIDIA Isaac Lab, MuJoCo, ORBIT-Surgical, dVRK, and agentic/generative AI frameworks.
Kevin Kawchak· Zenodo (CERN European Organi...· 0 citations
ABSTRAK Studi ini melakukan audit forensik terhadap degradasi pendapatan sistemik dalam ekosistem penerbitan digital global. Studi ini secara kritis mengkaji normalisasi narasi AdSense sebagai Uang Saku, yang secara agresif diperkuat oleh algoritma Kecerdasan Buatan (AI). Dengan menggunakan pendekatan Sosio-Legal dan pengambilan sampel digital, penelitian ini berpendapat bahwa narasi tersebut bukanlah nasihat keuangan yang netral, melainkan bentuk Gaslighting Institusional. Mekanisme ini berfungsi untuk menutupi monopoli lalu lintas yang dilakukan oleh Search Generative Experience (SGE) dan mengalihkan beban kegagalan sistemik kepada kreator individu (mengalihkan kesalahan). Studi ini mengusulkan strategi Kepatuhan Subversif, yang menganjurkan kedaulatan infrastruktur radikal untuk membongkar struktur feodalisme digital yang sedang muncul. Kata kunci: Gaslighting Institusional, Monopoli Algoritma, SGE, Feodalisme Digital, Kedaulatan Aset. 📢 BACA VERSI LENGKAP & DISKUSI INTERAKTIF: Ingin membaca analisis ini dengan bahasa yang lebih ringan dan studi kasus nyata? Kunjungi artikel selengkapnya di Blog Resmi Sosiolegal.com: KunciPro Research Institute - Membongkar Kebenaran, Melawan Arus.
TRI HAKIM· Zenodo (CERN European Organi...· 0 citations
We classify regular full-dimensional stochastic containment among binary standard semi-directed strongly tree-child level-2 phylogenetic networks under the Kimura two-parameter (K2P) model. On the principal positive Fourier domain D₊ = {(s,g): 02s−1}, a directed containment germ exists if and only if the two labelled networks are isomorphic after independently redirecting ordinary three-cycle factors. The same condition is equivalent to a common full-dimensional regular germ; in particular, no proper one-sided containment occurs. It follows that the semi-directed topology is generically identifiable modulo ordinary triangle redirection, and that its structural triangle class is exactly reconstructible away from a proper algebraic exceptional set. The proof combines displayed-quartet inequalities and exact whole-map identities, an exact two-sector bridge-fibre theorem, physical marginal submersions, localization, and a bounded graph-to-algebra classification of cycle and theta factors. The bounded classification is computer-assisted: every directed primitive relation, rank exclusion, restoration parent, transport, and one-/two-port probe is represented by an exact certificate with independent replay and mutation evidence. The classification transfers to the strict continuous-time domain 0<s<1, s²<g<1. For every n≥3, two weakly but not strongly tree-child level-2 networks have continuous-time K2P images sharing a regular germ of dimension 4n−3, proving sharpness of strong tree-childness. This record is the complete v1.0.5-r1 priority and reproducibility package: the 26-page article, 24-page reader supplement, compile-complete five-file source archive, deterministic 495-member referee/verifier archive, external archive-qualification report, checksum sidecars, and dual-license notice. The manuscript source is v1.0.5; revision r1 repairs only an auxiliary probe-current semantic binding and changes neither the theorem, manuscript, PDFs, nor frozen classification. The clean verifier replay passed 41/41 layers, and the focused semantic mutation suite rejected 20/20 attacks. Exact source bindings: package tag k2p-same-referee-package-v1.0.5-r1; annotated tag object 6c9c89d38f4f4cdc9c328d8bb1237458c617136d; commit e2f6e32e6fe885e90c8e83a8c5b00785e663a4ae; referee archive SHA-256 4564cd1f8cd95f670a2e0d9619babaf3c343762cfd8ceeb190cd17df72802889. Article, supplement, and certificate data are licensed under CC BY 4.0; verifier and build code are licensed under MIT. No specific funding supported this work. The author declares no competing interests. Generative-AI assistance and its verification workflow are disclosed in the article. No mixed-sign K2P classification is claimed.r
Alec Kriebel· Zenodo (CERN European Organi...· 2 citations
The deflated-Welch statistic: a closed-form, guaranteed-level test for heteroscedastic one-way ANOVA William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.21908169. What this is The reproducibility deposit for the deflated-Welch statistic T_BB, a closed-form, guaranteed-level test for heteroscedastic one-way ANOVA (the Behrens–Fisher problem for k ≥ 3 groups). Welch's test becomes liberal under skew and unstable variance weights at small samples; T_BB = Q(s²)·exp(−R) keeps the ordinary group means and buys a guaranteed level by deflating the Welch quadratic by a Berger–Boos scale-inflation radius R. Three operating points are provided: a fixedcalibrated radius (κ_s), a design-adaptive near-guarantee radius (closed-form polygamma Cornish–Fisher with a finite-nkurtosis guard), and a fully proved smallest-eigenvalue radius R_eig (Gaussian, extended under bounded kurtosis). What the deposit contains Manuscript (author + anonymized) and a derivations supplement (DA1–DA13) plus a long-form derivations companion, covering: why Welch fails under skew in closed form; the Berger–Boos deflation and its exact worst-case radius; the polygamma-cumulant Cornish–Fisher radius with saddlepoint-exact normal backbone; the excess-kurtosis tail term with its finite-n upper-confidence guard; the imbalance correction; the fully proved smallest-eigenvalue radius (with the k-group multiplicity fix, free-β optimization, and the proved-under-bounded-kurtosis widening); and the k-sample Behrens–Fisher null distribution. Interactive demonstrator rerun_cochran/honest_anova.html — computes raw-mean Welch, the fixed / adaptive / proved T_BB radii, the estimand-changing transform routes, and the full routing receipt in the browser, reproducing the deposited Python. Its engine is extracted as a standalone Node module (m01A_anova_engine.js) and checked cell-by-cell against Python across an 84-design taxonomy (verify_anova_engine_taxonomy.py/.js, max |Δp| = 0.00000). Reproducibility scripts (rerun_cochran/, rerun/) — every reported number traces to a named, deterministically-seeded script (size/power/surface, the calibration and information-limit decompositions, the proved-radius verification, the imbalance calibration, the skew-router branch, and the figures). Real-data evidence — anova_flip_scan.py scans 2,783 public one-way layouts (254 datasets): guaranteed T_BBwithholds ~41% of Welch-significant calls, concentrated where the weight-instability screen fires, and never manufactures significance (Table 7 / Figure 15). Figures and the deterministic deposit builder (fixed timestamps → stable md5). All evaluation is simulation-based; the one empirical component is the public-dataset scan, which uses only openly distributed data. Code is released under the MIT License; text and figures under CC BY 4.0. Version history (consolidated changelog) Published version DOIs are marked ✅; the concept DOI above always resolves to the latest. Staged versions were rolled into the next published one unless noted. v1.0.77 ✅ 10.5281/zenodo.22167690 (2026-08-30): CSDA guide-for-authors conformance — abstract trimmed to 247 words (from 284), keywords cut to 7 (from 11), the withholding highlight shortened to ≤85 characters, and the arXiv PDF/source regenerated. No change to methods, results, figures, or code. v1.0.76 ✅ 10.5281/zenodo.22167536 (2026-08-30) — AI-disclosure heading aligned to Elsevier. The manuscript's declaration heading is now "Declaration of generative AI and AI-assisted technologies in the manuscript preparation process" (was "Use of generative AI"); the disclosure body is unchanged. Prepared alongside an Elsevier-compliant cover-letter variant and an EM suggested-reviewer sheet (both kept outside the deposit). docx/pdf rebuilt; deterministic md5 refreshed. v1.0.75 ✅ 10.5281/zenodo.22167304 (2026-08-30) — Submission-sharpening pass. Graphical abstract + Elsevier Highlights; figures and tables renumbered into reading order with per-table Source clauses; the validity–power frontier (Figure 8) now carries the proved R_eig operating point (100% validity, size-adjusted power 0.613, merge_tbb_proved_frontier.py); new Section 7 "Recovering power by design" + Table 8 (rc_anova_power_by_design.py); and a live required-n calculator in honest_anova.html (per-group and total n for 80% power, "power now @ total n"), with a numeric-heading CSS fix and the engine re-verified against Python at 0.00000. v1.0.74 ✅ 10.5281/zenodo.22165892 (2026-08-29) — Proved-under-bounded-kurtosis radius (DA12.6). The proved non-normal widening now keys on excess kurtosis, √(1 + κ̂·(n−1)/(2n)), from the exact Var(s²/σ²) = 2/(n−1) + κ/n, so symmetric heavy tails (Student-t) are covered where the old skew form √(1 + 0.75·skew²) under-covered; tbbProvedswitched to the kurtosis form across the demonstrator, engine, and Python truth (re-verified JS-vs-Python at 0.00000); new rc_anova_kurtosis_proof.py + deep-dive. v1.0.73 ✅ 10.5281/zenodo.22165709 (2026-08-29) — Reconstructed & verified demonstrator engine (standalone Node module + taxonomy verifier, max |Δp| = 0.00000 across 84 designs; Yuen zero-variance fix; T_BB-routed presets both directions); series-impact deep-dive (the corrected R_eig k-group multiplicity gap also reaches m03 and m01t). v1.0.72 (2026-08-29) — Title set to "The deflated-Welch statistic…"; corrected + optimized proved radius R_eig (β/k multiplicity fix + β-optimization, DA12); real-data Welch-vs-T_BB flip scan (2,783 layouts; Table 7 / Figure 15) + demonstrator imbalance-factor fix; long-form derivations companion. v1.0.71 / v1.0.70 (2026-08-21) — Zhang normal-reference comparator benchmarked on the efficiency frontier (valid on only 24% of designs, in the calibrated-liberal cluster); k = 2 adaptive-radius case-study fold (design-scaling vs shape-keying distinction). v1.0.69 ✅ 10.5281/zenodo.22035826 (2026-08-20) — HTML R1/R2 presentation pass + Figure 9 adaptive per-cluster label merge. v1.0.68 ✅ 10.5281/zenodo.22033737 (2026-08-20) — Companion consolidation into a single six-column Table 6; Figures 11–14 harmonized into one story. v1.0.67 / v1.0.65 / v1.0.60 (2026-08-19/20) — Guarded-reference naming-collision fix; the 40,000-replication expanded-frontier pin (Table 3 + Figure 8) with the symmetric-heteroscedastic skew-router branch; the mean-preserving lightened-R_eig do-not-use fallback. v1.0.59 ✅ 10.5281/zenodo.21995320 (2026-08-18) — Reporting standard + honest_anova.html demonstrator re-aligned to the current T_BB methods paper. v1.0.57 ✅ 10.5281/zenodo.21986847 (2026-08-17) — Reviewer-comprehension pass (multi-paragraph abstract, contributions list, trimmed captions); proved radius R_eig added as a Table 3 scorecard row; corner tail-index correction (N−k)/2 (low-order moments exist in every deployed design). v1.0.56–v1.0.49 (2026-08-16) — The k-sample Behrens–Fisher corner-distribution program: two-moment scaled-χ² corner reference, derived corner cumulants, the secular-eigenvalue law + closed CGF + power-law tail, consolidated into derivations DA13 with a prior-art/novelty audit. v1.0.48 ✅ 10.5281/zenodo.21963458 (2026-08-16) — The unifying λ(z) correction (a smooth instability-keyed deflation strength). v1.0.45 ✅ 10.5281/zenodo.21962965 (2026-08-16) — Atomic sparsity index + bootstrap-t edge hardening + shape-aware pooled standardized-residual bootstrap (SA-PSRB); multivariate transfer to m03. v1.0.44–v1.0.41 (2026-08-16) — Shape-moment re-injection order (skew is the sweet spot), validated and hardened pooled standardized-residual bootstrap, atomic weight-noise probes. v1.0.40 ✅ 10.5281/zenodo.21961667 (2026-08-16) — Log-domain weight-stabilization probe (negative for stabilization; clarifies the size-adjusted oracle ceiling); includes the oracle-power gap decomposition (≈92% conservatism, ≈8% estimation). v1.0.37 ✅ 10.5281/zenodo.21961327 (2026-08-16) — Residual-bootstrap qualification of the shoot-out + the first proved Gaussian smallest-eigenvalue radius R_eig (DA12, the p = 1 specialization of the m03 theorem). v1.0.36 (2026-08-15) — Figure 11 T_BB-region colour fix (amber, matching the routing figures). v1.0.27 ✅ 10.5281/zenodo.21908170 — Earlier published baseline of the deposit. Provenance: every number traces to a named, deterministically-seeded script listed in the manuscript Declarations; the demonstrator engine reproduces the deposited Python to max |Δp| = 0.00000 across the taxonomy verification. License. Code and scripts in the deposit are released under the MIT License; text and figures under CC BY 4.0. Reuse is permitted with attribution to the author and citation of the concept DOI above. How to cite. Dwyer, W. J. The deflated-Welch statistic: a closed-form, guaranteed-level test for heteroscedastic one-way ANOVA. Reproducibility deposit, Zenodo. https://doi.org/10.5281/zenodo.21908169
William Dwyer· Zenodo (CERN European Organi...· 2 citations
An engineering whitepaper documenting the construction of Baiyuan GEO Platform (2024–2026), a SaaS system for Generative Engine Optimization. The system helps brands be cited accurately and consistently across ChatGPT, Claude, Gemini, Perplexity, DeepSeek, and 15+ AI platforms. Coverage: seven-dimension AI citation-rate scoring algorithm, AI-Bot-friendly shadow document delivery (AXP) on customer-owned domains, Schema.org three-layer entity knowledge graph, closed-loop hallucination detection & auto-remediation, F12 three-layer structural optimizer (V1 rule-based + V3.1 dual-engine AutoGEO + E-GEO), rag-backend-v2 LLM hallucination hardening (six defense layers), and platform SSOT chain (brand_faq / page_type / alerts unification). v1.1.2 (this version): substantially expanded chapters 14, 15, 16 in both Traditional Chinese (zh-TW) and English (en) editions — added new sections covering early hand-tuning failure modes, bidirectional rollback design, placeholder guard trigger story, patch order causal chain analysis, cross-tenant cache privacy boundary, breadcrumb 404 ghost incident review (42 days, ~3000 ghost URLs), cross-microservice SSOT boundaries, and 5 engineering lessons (takeaways) per chapter — totaling ~13,000 additional words across 6 chapter files. Also adds LinkedIn launch announcement drafts (4 versions: zh-TW/en/ja personal + zh-TW company). v1.2.0 (this version): adds Part VI — three new chapters (Ch 17 cross-border China GEO with a Hong Kong edge node, UA routing, ICP-free central compliance and bidirectional AI visibility; Ch 18 AXP HTML Mirror-First semantic-HTML shadow documents; Ch 19 a five-layer cache-invalidation architecture for zero-touch propagation) in Traditional Chinese and English; backfills the Japanese edition to full parity (ja chapters 14–19 added); and expands Ch 13 (multimodal GEO) across all three languages with VideoObject GSC parity + origin backfill, a same-origin copyright filter, and sitemap image/video extensions. Languages: Traditional Chinese, English, and Japanese — all complete through chapter 19. License: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).
Vincent Lin· Zenodo (CERN European Organi...· 3 citations
