{"id":"W3103996020","doi":"10.6084/m9.figshare.2082733.v2","title":"A Multiresolution Stochastic Process Model for Predicting Basketball Possession Outcomes","year":2016,"lang":"en","type":"article","venue":"Figshare","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Basketball; Process (computing); Econometrics; Possession (linguistics); Computer science; Operations research; Statistics; Mathematics; Geography; Linguistics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000095982,0.0001211567,0.0002089243,0.00009303525,0.0001185798,0.00003768392,0.0001579314,0.00007963603,0.01018999],"category_scores_gemma":[0.000651615,0.00009312399,0.00009655257,0.00007165461,0.000004812706,0.0002748384,0.0000355769,0.00004767899,0.0004636669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005581644,"about_ca_system_score_gemma":0.00002811267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006802169,"about_ca_topic_score_gemma":0.000009845365,"domain_scores_codex":[0.9990773,0.000001225769,0.0003364142,0.0002930343,0.00003718451,0.000254882],"domain_scores_gemma":[0.9993421,0.00006857598,0.0002615961,0.000188634,0.00007366481,0.00006546658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003633108,0.0009296642,0.3205615,0.002976671,0.0004462017,0.00001041179,0.004229262,0.3041801,0.0001093055,0.02294531,0.3122603,0.03098802],"study_design_scores_gemma":[0.0005293461,0.00002513824,0.01252216,0.0004595828,0.000003170101,6.985432e-7,0.00000864471,0.9808535,0.00001239174,0.002172562,0.003227029,0.0001857931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.08562933,0.000902155,0.1099195,0.001425753,0.0004909625,0.001791409,0.795577,0.0003445112,0.003919318],"genre_scores_gemma":[0.9942452,0.000003281728,0.0001635872,0.0001112956,0.00008782023,0.0002427921,0.003239475,0.00002475911,0.001881841],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9086158,"threshold_uncertainty_score":0.9907148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09006782663507686,"score_gpt":0.2779170278701033,"score_spread":0.1878492012350265,"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."}}