{"id":"W4385270131","doi":"10.1136/bmjebm-2023-112482","title":"Exploring advanced methods for network meta-analysis","year":2023,"lang":"en","type":"editorial","venue":"BMJ evidence-based medicine","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute for Work & Health; St. Michael's Hospital","funders":"","keywords":"Network analysis; Computer science; Engineering","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":"not_applicable","genre":"editorial","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"editorial","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1066107,0.0059439,0.01153329,0.00963712,0.001936121,0.01508748,0.008928819,0.01514539,0.016272],"category_scores_gemma":[0.4552274,0.003251428,0.01154745,0.008108723,0.00387024,0.00707931,0.004015996,0.02575446,0.005869213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004011615,"about_ca_system_score_gemma":0.008274493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003573569,"about_ca_topic_score_gemma":0.007127847,"domain_scores_codex":[0.9009895,0.07152584,0.008926016,0.002680838,0.01533126,0.0005465364],"domain_scores_gemma":[0.4431702,0.5048618,0.006341643,0.007626052,0.03561454,0.002385676],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00098986,0.00005440849,0.0001545379,0.02609394,0.009585236,0.0002388541,0.000188388,0.001346486,0.0002038907,0.008024836,0.8968332,0.05628648],"study_design_scores_gemma":[0.008480045,0.0004108321,0.001191992,0.04016592,0.03378663,0.0005863646,0.0002220061,0.02803015,0.0008352428,0.2039321,0.6817302,0.000628514],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0002347539,0.0949126,0.04082438,0.05918327,0.8001136,0.000678939,0.001214448,0.001081353,0.001756755],"genre_scores_gemma":[0.007398041,0.08385216,0.08202378,0.05635626,0.7572138,0.002962198,0.000769945,0.001524375,0.007899409],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.8933893,"threshold_uncertainty_score":0.563818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9687966746492905,"score_gpt":0.6861621719315322,"score_spread":0.2826345027177584,"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."}}