{"id":"W2900904000","doi":"10.1186/s13012-018-0836-4","title":"T-CaST: an implementation theory comparison and selection tool","year":2018,"lang":"en","type":"article","venue":"Implementation Science","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":220,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa; University of Toronto; St. Michael's Hospital","funders":"National Center for Advancing Translational Sciences; National Center for Chronic Disease Prevention and Health Promotion; National Institute of Diabetes and Digestive and Kidney Diseases; National Cancer Institute; National Institute of Mental Health; Centers for Disease Control and Prevention","keywords":"Health informatics; Health administration; Medicine; Health services research; Selection (genetic algorithm); Public health; Nursing; Artificial intelligence; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01023418,0.0001991707,0.0002175723,0.0005473027,0.004403527,0.0001554543,0.0004172982,0.00006199097,0.006022273],"category_scores_gemma":[0.000551055,0.00019283,0.00002100222,0.001851377,0.0008843552,0.002709371,0.0001982746,0.0002412763,0.0004139369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004929331,"about_ca_system_score_gemma":0.00159673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008127508,"about_ca_topic_score_gemma":0.004069735,"domain_scores_codex":[0.9946129,0.001097279,0.001280841,0.0007562437,0.001075307,0.001177404],"domain_scores_gemma":[0.9969428,0.0007287729,0.0006536907,0.000288495,0.0009670379,0.0004192459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008864656,0.00003890931,0.5491061,0.00005279698,0.0000103233,4.573756e-7,0.08023345,0.000001739693,0.07597953,0.0650728,0.007672558,0.2217427],"study_design_scores_gemma":[0.002578824,0.0008799389,0.8329042,0.00001843175,0.00002396688,0.000009346033,0.1025637,0.001044583,0.01524582,0.005227833,0.03910251,0.00040081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973979,0.000004155832,0.02032727,0.001682488,0.0006240302,0.001619223,0.00006196493,0.0001671165,0.001534746],"genre_scores_gemma":[0.9831361,0.000005940599,0.006600749,0.009299523,0.0005002761,0.000278266,0.00002236757,0.00001920659,0.0001375261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2837981,"threshold_uncertainty_score":0.9968926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7157988446021767,"score_gpt":0.7807871472186867,"score_spread":0.06498830261651001,"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."}}