{"id":"W6939853692","doi":"10.6084/m9.figshare.26708897","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":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological 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":[0.02967014,0.001734797,0.002649646,0.005907506,0.001136265,0.003693335,0.003943876,0.003604192,0.8281309],"category_scores_gemma":[0.3643673,0.001966406,0.003822122,0.00792156,0.0008036543,0.003183131,0.002774159,0.002533697,0.08240241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001871492,"about_ca_system_score_gemma":0.006259566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004754248,"about_ca_topic_score_gemma":0.008373668,"domain_scores_codex":[0.9835815,0.008497491,0.004033905,0.001803558,0.001597824,0.0004856611],"domain_scores_gemma":[0.4403301,0.5220347,0.01033012,0.01519223,0.01058619,0.001526619],"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":[0.0009646032,0.0001285357,0.003132483,0.03678326,0.001026081,0.0001666968,0.0002704334,0.001834423,0.0001374096,0.006360313,0.9243243,0.02487146],"study_design_scores_gemma":[0.02370474,0.0005800168,0.02120306,0.02956523,0.003399698,0.001170665,0.0005752059,0.008700132,0.001529586,0.09149741,0.8175541,0.0005202255],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002855249,0.0001483144,0.008521548,0.0006547988,0.0001745178,0.001243098,0.9858583,0.001481581,0.001632291],"genre_scores_gemma":[0.03380217,0.001159101,0.1608841,0.006348532,0.0007818068,0.07953338,0.6887756,0.00701889,0.02169636],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9703299,"threshold_uncertainty_score":0.2451504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8015145253608994,"score_gpt":0.5348226973406508,"score_spread":0.2666918280202486,"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."}}