{"id":"W2406430614","doi":"10.1016/j.jval.2016.03.807","title":"EARLY STAGE CLINICAL RESEARCH STUDIES IN CANADA: AN ANALYSIS OF THE ECONOMIC IMPACTS OF ATTRACTING MORE STUDIES: A CASE STUDY FOR MONTREAL","year":2016,"lang":"en","type":"article","venue":"Value in Health","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"InterDigital (Canada); Montréal InVivo; Université de Montréal","funders":"","keywords":"Metropolitan area; Private sector; Business; Economic growth; Medicine; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005187931,0.0005083658,0.0006002162,0.003627237,0.009440088,0.005124957,0.002623931,0.002369355,0.007704092],"category_scores_gemma":[0.01523486,0.0004515254,0.0008953123,0.008082681,0.002642876,0.001105159,0.002793541,0.002098192,0.0002367655],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1483692,"about_ca_system_score_gemma":0.1873444,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.993942,"about_ca_topic_score_gemma":0.9975699,"domain_scores_codex":[0.9932822,0.001735888,0.0001692255,0.0002670575,0.001366184,0.003179418],"domain_scores_gemma":[0.9671536,0.009372163,0.002231305,0.0006058704,0.009036312,0.01160083],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002930535,0.002023141,0.7011355,0.00122979,0.0008254893,0.01004226,0.02718474,0.01129695,0.004719261,0.07397314,0.03590928,0.1287299],"study_design_scores_gemma":[0.0004697729,0.0006848646,0.9005026,0.0005637772,0.0004103777,0.0006614542,0.04677204,0.007356183,0.0007573303,0.002804038,0.0388114,0.0002061819],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9358837,0.00593472,0.00150502,0.0176669,0.0000595678,0.0008187538,0.001978179,0.00007051213,0.03608274],"genre_scores_gemma":[0.9841769,0.001862919,0.001557145,0.001360824,0.00002432957,0.0001189609,0.0004942417,0.0000243783,0.01038045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9948121,"threshold_uncertainty_score":0.987771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8626377847964892,"score_gpt":0.6304865484119047,"score_spread":0.2321512363845846,"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."}}