{"id":"W2736965054","doi":"10.4103/efh.efh_4_16","title":"“In our own words”: Defining medical professionalism from a Latin American perspective","year":2017,"lang":"en","type":"article","venue":"Education for Health","topic":"Innovations in Medical Education","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Perspective (graphical); Latin Americans; Psychology; Sociology; Epistemology; Political science; Computer science; Philosophy; Artificial intelligence; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.001026421,0.0001183964,0.0003023584,0.0002038265,0.0004659712,0.00003037539,0.000203442,0.00009558293,0.0002186198],"category_scores_gemma":[0.008213985,0.0001069625,0.00004710338,0.00022684,0.0001120615,0.0001323735,0.00003325743,0.0004384916,0.00005425132],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00083704,"about_ca_system_score_gemma":0.007306929,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006981078,"about_ca_topic_score_gemma":0.0003708909,"domain_scores_codex":[0.9983225,0.00006556552,0.0004915198,0.0003392139,0.0004824194,0.000298727],"domain_scores_gemma":[0.9983228,0.00009019932,0.000544083,0.0005192106,0.0003451238,0.0001785514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002587976,0.002252376,0.09739912,0.000201382,0.0000505184,0.00000257752,0.03071761,4.825671e-7,0.00002104574,0.1105068,0.3932666,0.3653227],"study_design_scores_gemma":[0.002131284,0.0002990804,0.8084977,0.001307145,0.00002488898,0.0000120596,0.07760115,0.0005778581,0.0000311967,0.01601148,0.09326092,0.0002451795],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.412391,0.0002084562,0.000523635,0.5810333,0.002927451,0.0007977413,0.00001483684,0.00003370159,0.002069821],"genre_scores_gemma":[0.9400002,0.00003389737,0.02700115,0.0281713,0.001382857,0.000435835,0.0002654019,0.00002835354,0.00268101],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7110986,"threshold_uncertainty_score":0.9996315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04846905135496461,"score_gpt":0.5021909152711173,"score_spread":0.4537218639161527,"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."}}