Oct 2026· Zenodo (CERN European Organization for Nuclear Research)
Neuroethics, Human Enhancement, Biomedical InnovationsPsychometric Methodologies and Testing
Abstract
Data, R analysis code, and derived results for the psychometric evaluation of the German-language nine-item Transhumanism Scale (THS-9). The dataset comprises two independent samples (N = 200 and N = 1,051). Analyses include ordinal exploratory factor analysis, cross-validated ordinal confirmatory factor analysis, graded-response item response theory, reliability estimation, bootstrap confidence intervals, and response-category sensitivity analyses. The larger sample uses a fixed calibration/holdout split of 526/525 participants. The archive contains de-identified item responses, analysis and scoring code, fitted model objects, derived results, vector figures, software and session information, and reproduction instructions. Responses are coded −1 (disagree), 0 (uncertain/neutral), and +1 (agree); the original German middle response option is "unsicher/neutral".
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
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A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
