{"id":"W3155967961","doi":"10.1186/s42234-021-00066-8","title":"How artificial intelligence can help us ‘Choose Wisely’","year":2021,"lang":"en","type":"article","venue":"Bioelectronic Medicine","topic":"Healthcare cost, quality, practices","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women's College Hospital; Trillium Health Centre; University of Toronto; Canada Research Chairs; Toronto Public Health; University of King's College","funders":"","keywords":"Workflow; Leverage (statistics); Computer science; Clinical decision support system; Artificial intelligence; Knowledge management; Decision support system; Risk analysis (engineering); Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01089412,0.00119818,0.0006870993,0.002679702,0.00246664,0.01397028,0.00171928,0.006024141,0.01061271],"category_scores_gemma":[0.0251397,0.000470509,0.0008648072,0.001455393,0.01853898,0.01481113,0.005096909,0.007299187,0.004850199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002437434,"about_ca_system_score_gemma":0.004653111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003211084,"about_ca_topic_score_gemma":0.003563931,"domain_scores_codex":[0.9909267,0.00524589,0.0003575176,0.0008399244,0.002060235,0.0005695676],"domain_scores_gemma":[0.9843872,0.01106572,0.0007188428,0.001471252,0.001432511,0.0009245321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000059463,0.0001754271,0.002890854,0.000880204,0.0002522245,0.0002718541,0.004598325,0.003562901,0.0007925573,0.7357829,0.1229365,0.1277968],"study_design_scores_gemma":[0.00001642143,0.00003337811,0.0004632547,0.000523548,0.00002982946,0.0001541599,0.001487038,0.001257176,0.0003283775,0.7496095,0.2460486,0.00004875243],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.008188351,0.03099725,0.1342341,0.5542067,0.005421347,0.0001572384,0.000328675,0.0008717227,0.2655946],"genre_scores_gemma":[0.4282304,0.06806124,0.3035729,0.1295428,0.005779933,0.0005860644,0.0007433328,0.001005966,0.06247728],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01397028,"threshold_uncertainty_score":0.05761433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.609484213104878,"score_gpt":0.5433396321805208,"score_spread":0.06614458092435715,"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."}}