{"id":"W4404808374","doi":"10.1370/afm.22.s1.6574","title":"Improving comprehensive primary care training and practice through an interprofessional collaborative table","year":2024,"lang":"en","type":"article","venue":"The Annals of Family Medicine","topic":"Interprofessional Education and Collaboration","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Primary care; Table (database); Training (meteorology); Medical education; Medicine; Psychology; Nursing; Computer science; Family medicine; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02556655,0.0003723904,0.0003793072,0.0027129,0.007910816,0.008478839,0.002478704,0.001016404,0.006081608],"category_scores_gemma":[0.03383822,0.0005546874,0.0007014868,0.003046343,0.002665115,0.0055829,0.01480816,0.002001413,0.0009772568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01413248,"about_ca_system_score_gemma":0.05155413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03760125,"about_ca_topic_score_gemma":0.09938159,"domain_scores_codex":[0.9729668,0.01753933,0.001079238,0.001772676,0.00374227,0.002899606],"domain_scores_gemma":[0.9625606,0.01167484,0.003128444,0.004756724,0.005619896,0.01225942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001712902,0.001872523,0.09160782,0.001736398,0.000135854,0.0007496533,0.1930597,0.001872744,0.002047909,0.01073842,0.04939335,0.6466143],"study_design_scores_gemma":[0.0003537352,0.002000148,0.292312,0.00397681,0.0001987056,0.0008989533,0.370799,0.005945649,0.003965418,0.01726731,0.3020045,0.0002776959],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7453954,0.001553556,0.08761317,0.04778169,0.0005273047,0.009589987,0.002606131,0.00127287,0.1036599],"genre_scores_gemma":[0.8353577,0.0008311732,0.1513684,0.002361855,0.00007672195,0.003508215,0.001065818,0.00008392095,0.005346267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03760125,"threshold_uncertainty_score":0.1352105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2893960197155978,"score_gpt":0.5501500667443939,"score_spread":0.2607540470287961,"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."}}