{"id":"W4284973546","doi":"10.1016/j.cjca.2022.07.001","title":"Big Data, Big Expectations, and Big Judgements","year":2022,"lang":"en","type":"letter","venue":"Canadian Journal of Cardiology","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Fonds de Recherche du Québec - Santé","keywords":"Medicine; Big data; Data science; Data mining","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0004600056,0.0002792981,0.0011209,0.000988549,0.000149198,0.00003856877,0.0006758602,0.0003250584,0.0001706985],"category_scores_gemma":[0.0005957087,0.000272929,0.0002001603,0.0002186299,0.0002700672,0.00005770161,0.0001420928,0.001731099,0.00002362947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00035512,"about_ca_system_score_gemma":0.004285975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000888928,"about_ca_topic_score_gemma":0.00198702,"domain_scores_codex":[0.9976131,0.00043857,0.0006197655,0.000435671,0.0003544265,0.0005384153],"domain_scores_gemma":[0.9973873,0.0001584941,0.0004389401,0.001065606,0.0002523056,0.0006973528],"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":[0.00003462076,0.00000125379,0.01092591,0.0000744079,0.000813441,0.01019832,0.00004595243,0.000005830811,0.00000315754,0.000001692317,0.9488903,0.02900506],"study_design_scores_gemma":[0.0009161977,0.0002094284,0.01059358,0.00006263681,0.0004745975,0.002709155,0.000186753,0.000001751142,6.674523e-7,0.00003474547,0.9845956,0.0002149182],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01144549,0.03992326,0.0009829358,0.8468423,0.03895459,0.001300727,0.03803957,0.00006389833,0.02244721],"genre_scores_gemma":[0.1522515,0.001666345,0.0004966214,0.686022,0.1243056,0.00005825813,0.03048569,0.0003358055,0.004378189],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1608204,"threshold_uncertainty_score":0.9999723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06016978306376249,"score_gpt":0.2742516842905037,"score_spread":0.2140819012267412,"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."}}