{"id":"W4408298481","doi":"10.1186/s12874-025-02499-0","title":"Ranking of treatments in network meta-analysis: incorporating minimally important differences","year":2025,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Ranking (information retrieval); Statistics; Bayesian network; Mathematics; Computer science; Medicine; 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":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.7238237,0.000348767,0.01336677,0.002933482,0.0001788623,0.0002052113,0.003781738,0.0003677366,0.01932284],"category_scores_gemma":[0.6338161,0.0001545757,0.005188153,0.0134943,0.0006662983,0.0001035451,0.0007935247,0.0007560559,0.00009995794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006113246,"about_ca_system_score_gemma":0.001492526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004964844,"about_ca_topic_score_gemma":0.008358,"domain_scores_codex":[0.4498126,0.4925599,0.02861714,0.002949669,0.0245547,0.001506009],"domain_scores_gemma":[0.4145862,0.5683295,0.007341746,0.005900743,0.003170358,0.0006714995],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001209272,0.0002230218,0.8751851,0.0001544621,0.06866177,0.00007479009,0.0003967324,0.0003141614,0.00007798406,0.0354734,0.003446739,0.01587094],"study_design_scores_gemma":[0.00142731,0.0004005556,0.3215086,0.0001585876,0.0950321,0.00001098426,0.003758712,0.08052804,0.0001191859,0.4940895,0.002496807,0.0004695958],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3205592,0.02901917,0.6310214,0.003363881,0.0004159055,0.00204816,0.00001807595,0.00001135007,0.01354283],"genre_scores_gemma":[0.7503509,0.0001796808,0.2428867,0.0002602969,0.00007900367,0.0003073032,0.000008682111,0.000009817787,0.005917641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5536765,"threshold_uncertainty_score":0.9815736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9728456260694304,"score_gpt":0.7115555423479419,"score_spread":0.2612900837214884,"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."}}