{"id":"W2905992589","doi":"10.1186/s12874-018-0641-4","title":"Mechanisms, contexts and points of contention: operationalizing realist-informed research for complex health interventions","year":2018,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hôpital Charles-Le Moyne; Sinai Health System; Trillium Health Centre; Université de Montréal; Lunenfeld-Tanenbaum Research Institute; University of Toronto; Université de Sherbrooke; Women's College Hospital","funders":"Canadian Institutes of Health Research; University of Toronto; Massey University; Health Research Council of New Zealand; Université de Montréal; Université de Sherbrooke","keywords":"Operationalization; Psychological intervention; Health services research; MEDLINE; Psychology; Medicine; Data science; Computer science; Public health; Epistemology; Nursing; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2659313,0.002615554,0.003274122,0.01609177,0.0120895,0.03168847,0.009101016,0.0106231,0.008968215],"category_scores_gemma":[0.315111,0.003328586,0.004239715,0.007631574,0.1434877,0.04971329,0.02591665,0.01040968,0.0006180851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02922233,"about_ca_system_score_gemma":0.03263493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003551633,"about_ca_topic_score_gemma":0.003538592,"domain_scores_codex":[0.6578507,0.3005074,0.008694351,0.01474617,0.01330355,0.004897837],"domain_scores_gemma":[0.5149488,0.4071427,0.03074077,0.03354853,0.00992592,0.003693357],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005672859,0.0000525887,0.002802399,0.0008449546,0.0001235984,0.0001656884,0.02465305,0.001874093,0.0001046275,0.9587155,0.0003367255,0.01027013],"study_design_scores_gemma":[0.00007927878,0.00007786798,0.001249954,0.001496465,0.0001332284,0.0001165808,0.01674768,0.003146121,0.0002751571,0.9704683,0.006160317,0.00004890116],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09486468,0.01236534,0.6962724,0.09163383,0.001123784,0.004832666,0.0003367439,0.0003586583,0.09821189],"genre_scores_gemma":[0.8337356,0.001582824,0.1567938,0.001937468,0.0001817969,0.005003604,0.00006902806,0.00007895004,0.0006169158],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7340688,"threshold_uncertainty_score":0.9052374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9855169283511372,"score_gpt":0.8505520599018759,"score_spread":0.1349648684492614,"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."}}