{"id":"W3163627433","doi":"10.1002/dta.3058","title":"Frequency and type of adverse analytical findings in athletics: Differences among disciplines","year":2021,"lang":"en","type":"article","venue":"Drug Testing and Analysis","topic":"Doping in Sports","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"World Anti-Doping Agency","keywords":"Athletes; Adverse effect; Anabolic-Androgenic Steroids; Psychology; Set (abstract data type); Medicine; Demography; Physical therapy; Internal medicine; Anabolism; Computer science; Sociology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.002331079,0.0002530639,0.000520331,0.002375746,0.0004346512,0.0008341642,0.0005735666,0.0005147613,0.001589539],"category_scores_gemma":[0.007366418,0.0001803292,0.0005835996,0.001372148,0.0007803802,0.000642703,0.001032612,0.0005129309,0.0003502033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003399552,"about_ca_system_score_gemma":0.0004794814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002006458,"about_ca_topic_score_gemma":0.003071374,"domain_scores_codex":[0.9957268,0.0007926041,0.000713961,0.0008716285,0.001476286,0.000418763],"domain_scores_gemma":[0.9932107,0.00176155,0.003309362,0.0002925314,0.001011891,0.0004139605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004385349,0.00007793772,0.9827816,0.0001836221,0.00012747,0.0004413782,0.0003850413,0.00006797251,0.001934069,0.00005422705,0.0002321095,0.01327598],"study_design_scores_gemma":[0.000004587797,0.0003576255,0.9944431,0.00007003135,0.00006974209,0.002385519,0.0007797753,0.0001211585,0.000751727,0.00008936387,0.0009145931,0.0000127414],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919126,0.003147434,0.0008911943,0.0001426984,0.0000289285,0.00008844677,0.0007600257,0.00003103439,0.002997588],"genre_scores_gemma":[0.9966144,0.001329701,0.0007441221,0.0001094871,0.00002475907,0.00003003285,0.0005137234,0.00001236524,0.0006214983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002375746,"threshold_uncertainty_score":0.01232809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03819160249935151,"score_gpt":0.3174926745537808,"score_spread":0.2793010720544293,"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."}}