{"id":"W6902317696","doi":"10.6084/m9.figshare.26708897.v1","title":"Additional file 6 of Application of causal inference methods in individual-participant data meta-analyses in medicine: addressing data handling and reporting gaps with new proposed reporting guidelines","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Causal inference; Inference; Group method of data handling; Key (lock); 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":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0260624,0.001951442,0.002765536,0.006855381,0.001063384,0.004049062,0.003737126,0.003558116,0.8698037],"category_scores_gemma":[0.3416648,0.002229191,0.003762108,0.00829223,0.0007185778,0.003645855,0.002832221,0.002446141,0.1150056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002072479,"about_ca_system_score_gemma":0.006210282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004049277,"about_ca_topic_score_gemma":0.006570032,"domain_scores_codex":[0.9868133,0.006169323,0.003755322,0.001313728,0.001508569,0.0004397265],"domain_scores_gemma":[0.4832797,0.4764321,0.01160585,0.01385888,0.01321943,0.001604008],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009430555,0.0001200502,0.001794318,0.03216206,0.0006249332,0.0001196539,0.0001698399,0.001141683,0.00009619555,0.004507407,0.9356909,0.0226299],"study_design_scores_gemma":[0.02381563,0.0005056825,0.01416042,0.02937874,0.00245482,0.0008913964,0.0004236162,0.006624646,0.001505212,0.07926853,0.8405135,0.0004578113],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.0002262712,0.0001424186,0.006384523,0.0006779341,0.000182247,0.001276469,0.9873359,0.001880616,0.001893631],"genre_scores_gemma":[0.02419171,0.001420032,0.1347914,0.005868673,0.0009481661,0.07223532,0.729014,0.008507817,0.02302285],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9739376,"threshold_uncertainty_score":0.1857092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.986702206017277,"score_gpt":0.7198594874108595,"score_spread":0.2668427186064175,"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."}}