{"id":"W6930691774","doi":"10.5281/zenodo.15271939","title":"Code and Trained models of the work \"Dribble in the Mind: Exploring Causality with Cognitive Soccer Agents\"","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Wound Healing and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Construct (python library); Causality (physics); Cognition; Perception; Code (set theory); Cognitive model; Work (physics); Causal model","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004511665,0.0005250798,0.0002557259,0.0003884507,0.000383102,0.001077611,0.001638514,0.000939,0.01113332],"category_scores_gemma":[0.00250154,0.0003146179,0.0005135268,0.0003384281,0.0007594661,0.001041818,0.001142389,0.0009224613,0.002458864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007936259,"about_ca_system_score_gemma":0.001762796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009271258,"about_ca_topic_score_gemma":0.01069364,"domain_scores_codex":[0.9997991,0.00003312897,0.00001297697,0.00005218713,0.00007980173,0.00002283031],"domain_scores_gemma":[0.9991254,0.0002587397,0.00005940965,0.0002653415,0.0002458208,0.00004529469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000317058,0.0002539291,0.004201001,0.0002128819,0.0001064722,0.0003204119,0.0005234546,0.8426068,0.01267422,0.03713989,0.01076847,0.09087536],"study_design_scores_gemma":[0.00002170303,0.00002101264,0.0001983389,0.00001038899,0.00001013061,0.00002195333,0.00002334334,0.9852397,0.005215303,0.004456025,0.0047731,0.000008906633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.1735897,0.0001748618,0.7602711,0.000821153,0.0002589243,0.0004196188,0.00318419,0.02942808,0.03185247],"genre_scores_gemma":[0.7077667,0.0001843997,0.2623551,0.0001699827,0.00002266381,0.000487334,0.004019884,0.001927754,0.02306621],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01113332,"threshold_uncertainty_score":0.03724462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.131712709455424,"score_gpt":0.3007490680060913,"score_spread":0.1690363585506673,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}