{"id":"W4294740447","doi":"10.3384/ecp191005","title":"Scouting Automated Ratings Analyzing Habits (SARAH): A Statistical Methodology for Scouting and Player Development","year":2022,"lang":"en","type":"article","venue":"Linköping electronic conference proceedings","topic":"Sports Performance and Training","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Human–computer interaction; Software engineering; Artificial intelligence; Data science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002160392,0.0002958408,0.0005885224,0.0002867358,0.0009702534,0.00009638539,0.0001454615,0.0001015081,0.00009413402],"category_scores_gemma":[0.0004020739,0.0003050002,0.00005919797,0.0003768884,0.00008756575,0.0001757037,0.0001912478,0.00082775,0.0000017628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000312617,"about_ca_system_score_gemma":0.001083931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002214627,"about_ca_topic_score_gemma":0.000007226277,"domain_scores_codex":[0.9972343,0.00001474404,0.0006401557,0.0006737463,0.0003389585,0.001098056],"domain_scores_gemma":[0.9989782,0.0001939282,0.0003080289,0.00009159656,0.0002754481,0.0001527846],"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":[0.001998939,0.0003292841,0.5870983,0.002598139,0.001066767,0.00005600889,0.05576643,0.00008813792,0.08218923,0.07973041,0.0006507681,0.1884276],"study_design_scores_gemma":[0.01151071,0.004131331,0.1292551,0.001723871,0.0009902858,0.002031042,0.01884428,0.7833199,0.0250666,0.003633125,0.01709932,0.002394511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845249,0.0002891152,0.01284759,0.0005627017,0.0000882921,0.0007529677,0.000004599398,0.0005327124,0.0003971282],"genre_scores_gemma":[0.9468845,0.00001757287,0.05194456,0.0004704135,0.0001107907,0.0002993937,0.00006356863,0.00004768975,0.0001614897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7832317,"threshold_uncertainty_score":0.9999402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05951235377246135,"score_gpt":0.3362500826836334,"score_spread":0.2767377289111721,"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."}}