{"id":"W4366386740","doi":"10.1136/bmjebm-2022-112136","title":"Implementing hierarchical network meta-analysis incorporating exchangeable dose effects compared to standard hierarchical network meta-analysis","year":2023,"lang":"en","type":"article","venue":"BMJ evidence-based medicine","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of Calgary; St. Michael's Hospital","funders":"Medical Research Council","keywords":"Meta-analysis; Network analysis; Computer science; Multilevel model; Medicine; Internal medicine; Engineering; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch"],"domain":"methods","study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"},{"model":"gpt","categories":["metaresearch"],"domain":"methods","study_design":"theoretical_or_conceptual","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","metaepi_broad","bibliometrics","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["metaresearch","metaepi_narrow","metaepi_broad","insufficient_payload"],"category_scores_codex":[0.4064701,0.00160821,0.03597088,0.004751949,0.001437396,0.001429674,0.004517142,0.000302316,0.04573487],"category_scores_gemma":[0.103094,0.0007799066,0.0296387,0.06226423,0.000441193,0.0005983483,0.00127161,0.0009766486,0.001765965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001918039,"about_ca_system_score_gemma":0.000483733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003767307,"about_ca_topic_score_gemma":0.002349063,"domain_scores_codex":[0.8958602,0.05024116,0.02365024,0.004777538,0.02250937,0.002961467],"domain_scores_gemma":[0.8955351,0.07967909,0.01030448,0.009614623,0.003000953,0.001865742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.0001497659,0.00003986346,0.009009805,0.000182035,0.5720419,0.000168822,0.0003241336,0.2437434,0.00002429879,0.001193658,0.1719063,0.00121601],"study_design_scores_gemma":[0.0005251415,0.0003387349,0.003568034,0.00007837245,0.8590148,0.000004077555,0.0002365098,0.1056609,0.00001376469,0.00690715,0.02296294,0.0006895805],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009967649,0.03748539,0.8376179,0.1006939,0.001003042,0.01086223,0.0002304095,0.000309007,0.001830484],"genre_scores_gemma":[0.8612083,0.0001043377,0.1054084,0.01525389,0.003446046,0.003949984,0.0005708569,0.000148347,0.009909901],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8512406,"threshold_uncertainty_score":0.9998626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8066750011977708,"score_gpt":0.5551599690728524,"score_spread":0.2515150321249184,"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."}}