{"id":"W2168029400","doi":"10.3109/13561820.2012.719943","title":"Key trends in interprofessional research: A macrosociological analysis from 1970 to 2010","year":2012,"lang":"en","type":"article","venue":"Journal of Interprofessional Care","topic":"Interprofessional Education and Collaboration","field":"Health Professions","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Field (mathematics); Legitimacy; Interprofessional education; Thematic analysis; Sociology; Rhetoric; Data science; Social science; Psychology; Qualitative research; Political science; Computer science; Health care; Law; Politics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003891337,0.0003687465,0.0009620975,0.003364192,0.0007920877,0.00002962129,0.0008799685,0.0006322198,0.01217385],"category_scores_gemma":[0.001175535,0.0002583083,0.0005105156,0.003633441,0.0001502568,0.0006592124,0.0006409722,0.004163356,0.0006679449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001648411,"about_ca_system_score_gemma":0.001780263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008439207,"about_ca_topic_score_gemma":0.001968981,"domain_scores_codex":[0.9907118,0.003969014,0.002125201,0.0004289136,0.001631898,0.001133175],"domain_scores_gemma":[0.9934361,0.002242164,0.0008619038,0.0004542939,0.002186119,0.0008194164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006924011,0.00062951,0.839009,0.00003744722,0.000329743,0.00002771192,0.07466145,0.00003787622,0.01079369,0.001692196,0.06207117,0.003786135],"study_design_scores_gemma":[0.001114503,0.0002618247,0.8682284,0.002083889,0.0001240875,0.000005397006,0.1215982,0.00004494516,0.000179657,0.0006651062,0.005361353,0.0003326065],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738912,0.0009179267,0.0004354917,0.008172594,0.01295701,0.0003798374,0.0001539022,0.00002682166,0.003065245],"genre_scores_gemma":[0.9844412,0.00001515289,0.003985601,0.003296035,0.002604512,0.0001543339,0.000242044,0.00004125738,0.005219841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05670982,"threshold_uncertainty_score":0.9999869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1324974872292094,"score_gpt":0.5510653490257557,"score_spread":0.4185678617965463,"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."}}