{"id":"W3022623176","doi":"10.2147/clep.s242097","title":"&lt;p&gt;Synthetic and External Controls in Clinical Trials – A Primer for Researchers&lt;/p&gt;","year":2020,"lang":"en","type":"review","venue":"Clinical Epidemiology","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":258,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of British Columbia; Impact","funders":"","keywords":"Medicine; Critical appraisal; Control (management); Set (abstract data type); Key (lock); Computational biology; Computer science; Data science; Alternative medicine; Biology; Pathology; Artificial intelligence","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":["metaresearch"],"category_scores_codex":[0.327206,0.00238134,0.004203829,0.008774761,0.00147037,0.01205999,0.004750716,0.008403214,0.01228036],"category_scores_gemma":[0.5347183,0.001532869,0.003555567,0.01013181,0.01751256,0.01302071,0.006073091,0.01753507,0.00457323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006611439,"about_ca_system_score_gemma":0.01768797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002229945,"about_ca_topic_score_gemma":0.001824835,"domain_scores_codex":[0.6463249,0.3059716,0.01998364,0.005602858,0.02127302,0.0008440057],"domain_scores_gemma":[0.2373524,0.7031643,0.01721139,0.01945833,0.02139203,0.001421541],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002062604,0.00005525643,0.0004069796,0.0238504,0.0004671216,0.0001081145,0.00118704,0.001913916,0.0002035701,0.5125589,0.09296665,0.3660758],"study_design_scores_gemma":[0.0001917788,0.0001930917,0.0004926103,0.04598299,0.0002634272,0.0002284807,0.0004363004,0.003109107,0.0005218731,0.5227267,0.4257495,0.0001040146],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.000327969,0.4544345,0.3432151,0.1679209,0.01424203,0.002407986,0.0008871586,0.0006281464,0.01593613],"genre_scores_gemma":[0.02087354,0.3470403,0.5381942,0.04646432,0.02067012,0.0184388,0.0008125202,0.0009423048,0.006563938],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.672794,"threshold_uncertainty_score":0.8296748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9492111274371475,"score_gpt":0.7575105690970199,"score_spread":0.1917005583401277,"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."}}