{"id":"W6976945731","doi":"10.6084/m9.figshare.14788632.v1","title":"Additional file 1 of Most published meta-regression analyses based on aggregate data suffer from methodological pitfalls: a meta-epidemiological study","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Geotechnical and construction materials studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Aggregate (composite); Aggregate data; Data file; Component (thermodynamics); Data collection","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","metaepi_broad"],"domain":"methods","study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["insufficient_payload"],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","metaepi_broad","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01226401,0.002474087,0.003675562,0.006560817,0.001058316,0.003155905,0.003383442,0.002999817,0.8624851],"category_scores_gemma":[0.190237,0.002211483,0.007032104,0.009811962,0.0007917868,0.003148771,0.00212071,0.001774249,0.07728551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001603257,"about_ca_system_score_gemma":0.003534243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005656383,"about_ca_topic_score_gemma":0.01194889,"domain_scores_codex":[0.9929473,0.002627247,0.00224219,0.001080845,0.0007132181,0.0003891945],"domain_scores_gemma":[0.7384537,0.2317743,0.01362461,0.008070537,0.007140592,0.0009362937],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.002971651,0.0002196376,0.006087527,0.1404572,0.0072781,0.0002697107,0.0002304919,0.001633477,0.000190753,0.002745252,0.818293,0.01962321],"study_design_scores_gemma":[0.1062555,0.00139088,0.04600701,0.06710187,0.03595789,0.002333684,0.0009685481,0.006052773,0.001328634,0.03645929,0.6954559,0.000687986],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004139,0.000464354,0.001042249,0.0002474314,0.00009345594,0.0006261129,0.9958606,0.0002967968,0.0009551557],"genre_scores_gemma":[0.06158794,0.00239529,0.04490636,0.006681656,0.0008720589,0.0592976,0.7868556,0.003506117,0.03389736],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9963244,"threshold_uncertainty_score":0.1961483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5199242974097767,"score_gpt":0.3867582678563971,"score_spread":0.1331660295533796,"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."}}