{"id":"W2141327222","doi":"10.3109/13561820.2014.900001","title":"Leading team learning: what makes interprofessional teams learn to work well?","year":2014,"lang":"en","type":"article","venue":"Journal of Interprofessional Care","topic":"Interprofessional Education and Collaboration","field":"Health Professions","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Interprofessional education; Medical education; Team-based learning; Psychology; Knowledge management; Health care; Medicine; Computer science; Engineering; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002304933,0.0005386676,0.0009429859,0.0008982345,0.001536569,0.0001314242,0.0009640614,0.0005994613,0.003726766],"category_scores_gemma":[0.001941048,0.0003947169,0.0004299768,0.0009565583,0.000113197,0.001248529,0.0005214721,0.004097515,0.002602074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001244955,"about_ca_system_score_gemma":0.003411209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003163428,"about_ca_topic_score_gemma":0.0001126171,"domain_scores_codex":[0.992395,0.0024766,0.002187429,0.0005464095,0.001456565,0.0009379309],"domain_scores_gemma":[0.9925417,0.001719621,0.001649432,0.000444834,0.002864339,0.0007800176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.02120497,0.0007515153,0.3530203,0.0008593466,0.0003396271,0.00004094278,0.09931469,0.0008677196,0.01358704,0.006570076,0.4056238,0.09781996],"study_design_scores_gemma":[0.002771561,0.001823778,0.03075917,0.03747328,0.0001152339,0.00004277064,0.5610682,0.000220507,0.0009392783,0.001451835,0.3622394,0.001095031],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9286014,0.0007688496,0.003424578,0.01403045,0.03061094,0.0008894249,0.000006966294,0.0001215525,0.02154581],"genre_scores_gemma":[0.9340616,0.00004386705,0.003080914,0.009034301,0.003124801,0.0001137526,0.00005428551,0.0001049454,0.05038151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4617535,"threshold_uncertainty_score":0.9998505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01548800453087799,"score_gpt":0.40378940680537,"score_spread":0.3883014022744919,"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."}}