{"id":"W2093411079","doi":"10.1177/1098214010379038","title":"Evaluating the Science of Discovery in Complex Health Systems","year":2010,"lang":"en","type":"article","venue":"American Journal of Evaluation","topic":"Interdisciplinary Research and Collaboration","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Nutrasource; University of Toronto","funders":"","keywords":"Process (computing); Discipline; Plan (archaeology); Data science; Work (physics); Engineering ethics; Computer science; Scientific discovery; Management science; Logic model; Translational science; Health science; Sociology; Psychology; Engineering; Medicine; Social science; Medical education","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.174943,0.00121159,0.002318626,0.006500632,0.003260616,0.0113854,0.001767978,0.002378021,0.002902748],"category_scores_gemma":[0.3850008,0.0005507854,0.001560012,0.006591642,0.009825239,0.009418487,0.007536601,0.002618602,0.000188594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0142338,"about_ca_system_score_gemma":0.01528035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005463939,"about_ca_topic_score_gemma":0.004859953,"domain_scores_codex":[0.657289,0.3118983,0.006916304,0.003412491,0.01846792,0.002015992],"domain_scores_gemma":[0.3711487,0.5841909,0.01735689,0.009757331,0.01411246,0.003433753],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.002456707,0.002226433,0.08196265,0.005831198,0.00289207,0.0003843595,0.006033222,0.2780213,0.001054388,0.3566656,0.003736009,0.258736],"study_design_scores_gemma":[0.0006542319,0.008235364,0.02310676,0.002091086,0.001125777,0.0002390251,0.01088767,0.3692299,0.003323398,0.5690762,0.01176083,0.0002698804],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6285566,0.0144631,0.2477834,0.02431371,0.000682074,0.007189738,0.0009884919,0.0002538754,0.07576893],"genre_scores_gemma":[0.9082904,0.002227718,0.08634306,0.0005487455,0.0001139258,0.001750961,0.0001525313,0.00002146143,0.0005511542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.825057,"threshold_uncertainty_score":0.9251979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2891501171514995,"score_gpt":0.5838757997116935,"score_spread":0.2947256825601939,"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."}}