{"id":"W4210452204","doi":"10.2196/27691","title":"Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Healthcare cost, quality, practices","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Leverage (statistics); Government (linguistics); Health care; Conversation; Stakeholder; Medicine; Medical diagnosis; Nursing; Business; Public relations; Knowledge management; Psychology; Computer science; Artificial intelligence; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.01513297,0.000503848,0.000786003,0.00177582,0.003542002,0.01280654,0.00134011,0.005549562,0.01578265],"category_scores_gemma":[0.02999536,0.0007229201,0.0007959889,0.001522482,0.01052881,0.01453939,0.008087979,0.009126401,0.00436049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005333052,"about_ca_system_score_gemma":0.01261988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005967305,"about_ca_topic_score_gemma":0.005930771,"domain_scores_codex":[0.9904802,0.004480937,0.0004387454,0.0008868303,0.002873781,0.0008393999],"domain_scores_gemma":[0.9702235,0.01772126,0.001302327,0.00343538,0.00292082,0.004396675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001565438,0.0002511238,0.01010156,0.001472371,0.0001426498,0.0008240616,0.006682214,0.0007186757,0.001836906,0.4770179,0.2436965,0.2570994],"study_design_scores_gemma":[0.00006789765,0.0001690042,0.007694821,0.002013224,0.00005531771,0.001430107,0.00411051,0.001437253,0.0006953003,0.4317956,0.5504659,0.00006514824],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01255228,0.02333646,0.02934342,0.8001134,0.002698945,0.0001045734,0.0003996622,0.0004311772,0.13102],"genre_scores_gemma":[0.6385144,0.05387456,0.1014661,0.1668072,0.01168289,0.0005230664,0.0009708003,0.0004227303,0.02573824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01578265,"threshold_uncertainty_score":0.08003181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3390967474766703,"score_gpt":0.5433301557162067,"score_spread":0.2042334082395363,"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."}}