Oct 2026· Zenodo (CERN European Organization for Nuclear Research)
Digital Games and Media
Abstract
Grenade use in professional Counter-Strike follows community conventions written neither in the game's rules nor in its physics. We present an annotation schema for utility lineups, defined by an origin zone, a landing zone and a grenade type, and a de_dust2 lineup dataset built from 69,827 throws in 122 professional matches of the ESTA dataset. Four fields are computed without human input; three of them were tested against criteria registered before they were derived. Geometry and frequency are usable with stated limits. Generality met its registered criterion for being unusable (rho_MM = -0.217, p = 7.1e-5, 330 lineups) and is not used. Difficulty passed its gate on bucket count but failed its main test: the tier gap was -0.98 with a 95% cluster bootstrap interval of [-6.68, 2.94], so it is reported only as a description. The purpose of a throw (intent) and whether it is conventional are left to human annotators. We pre-register a test of whether a panel of large language models could replace them. Three experienced players and at least three vision-capable models will label the same 100 stimuli under identical instructions. Krippendorff's alpha with item-bootstrap intervals will be judged against thresholds of 0.5 and 0.7 through five branches with a fixed verdict order. We report the full registration history, including revisions that did not only tighten the plan and an AI-filled label file that was never used. No human label exists yet. Results will appear in a later version.
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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.