{"id":"W4385841173","doi":"10.46747/cfp.6908522","title":"Response to Lavergne et al","year":2023,"lang":"en","type":"letter","venue":"Canadian Family Physician","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Blame; Population; Medicine; Data science; Computer science; Psychiatry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001127889,0.0005559436,0.0008911764,0.001091397,0.0009864673,0.00003468842,0.0007938981,0.001087256,0.00006863357],"category_scores_gemma":[0.0001560144,0.0005956061,0.0002394703,0.0008510165,0.00005417884,0.0001134102,0.0001805226,0.005081854,0.03085452],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004700359,"about_ca_system_score_gemma":0.02220787,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1131366,"about_ca_topic_score_gemma":0.128346,"domain_scores_codex":[0.9939091,0.00153588,0.00069974,0.0008316687,0.0005562223,0.002467432],"domain_scores_gemma":[0.9956384,0.001534251,0.0002163223,0.001239008,0.0002447508,0.001127311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006072093,0.000003073054,0.00002537244,0.0001339008,0.00004314912,0.0008980982,0.0003622969,0.000001009256,0.00005173485,0.00009443382,0.99674,0.001586254],"study_design_scores_gemma":[0.0003135874,0.00008824499,0.005238734,0.000276128,0.0000251438,2.090488e-7,0.0003170165,0.000001115481,6.592706e-7,0.0002360831,0.9929171,0.0005860214],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0004609873,0.00009513813,0.000003225995,0.8100073,0.004798152,0.001139039,0.002295785,0.0002925173,0.1809079],"genre_scores_gemma":[0.00001829008,0.0000430933,0.0000550795,0.9152741,0.003661187,0.0004023417,0.001214452,0.0002883416,0.07904314],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1052668,"threshold_uncertainty_score":0.9996495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06968179586556575,"score_gpt":0.3920054766567614,"score_spread":0.3223236807911957,"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."}}