{"id":"W7081174541","doi":"10.5281/zenodo.16415564","title":"The Application of Artificial Intelligence Metrics in the National Basketball Association (NBA)","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Basketball; Transformative learning; Process (computing); Analytics; Association (psychology); Perspective (graphical); Wearable computer; Wearable technology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009084702,0.0005746073,0.0003476788,0.006324456,0.001424924,0.00518266,0.0008535713,0.0006308216,0.002629023],"category_scores_gemma":[0.04048,0.0001806817,0.0003298554,0.006640965,0.001007098,0.00218051,0.003295732,0.001164573,0.0006942311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005182114,"about_ca_system_score_gemma":0.00393853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03600875,"about_ca_topic_score_gemma":0.03059495,"domain_scores_codex":[0.9939269,0.002496237,0.0004310998,0.0007442879,0.002091599,0.0003099217],"domain_scores_gemma":[0.9732724,0.009950528,0.004207195,0.001283007,0.008782575,0.002504239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003783022,0.0004483235,0.7395855,0.0002435053,0.0001854962,0.000242251,0.00314136,0.02211936,0.0007784934,0.02135494,0.01269864,0.1988239],"study_design_scores_gemma":[0.00004007857,0.0006992741,0.7501938,0.0004126182,0.00007739726,0.0003037728,0.009643744,0.1630778,0.002174167,0.02334585,0.04992064,0.0001108758],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.901092,0.001282865,0.02702585,0.00477982,0.000310925,0.000344596,0.003443493,0.0005164588,0.06120383],"genre_scores_gemma":[0.9855736,0.0002161466,0.01107233,0.000104157,0.00003655944,0.0001086333,0.001253334,0.00004166189,0.001593636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03600875,"threshold_uncertainty_score":0.07159829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04022073928730948,"score_gpt":0.2704074663829129,"score_spread":0.2301867270956034,"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."}}