{"id":"W4386705315","doi":"10.1002/jrsm.1670","title":"How to plan and manage an individual participant data meta‐analysis. An illustrative toolkit","year":2023,"lang":"en","type":"article","venue":"Research Synthesis Methods","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Jewish General Hospital; McGill University; Université de Montréal; McGill University Health Centre","funders":"Institute of Genetics; Horizon 2020 Framework Programme","keywords":"Computer science; Harmonization; Plan (archaeology); Multinational corporation; Aggregate data; Data collection; Knowledge management; Work (physics); Data extraction; Meta-analysis; Process management; MEDLINE; Medicine; Business","routes":{"ca_aff":true,"ca_fund":true,"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","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["metaresearch","insufficient_payload"],"category_scores_codex":[0.6419351,0.0004466984,0.006525876,0.00348817,0.0006107278,0.006529439,0.007783369,0.0001582826,0.004131803],"category_scores_gemma":[0.2336036,0.0002223988,0.001448464,0.01271852,0.0002914874,0.00156376,0.002352447,0.0004414837,0.0009975251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001689532,"about_ca_system_score_gemma":0.0001100923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001042597,"about_ca_topic_score_gemma":0.0006289337,"domain_scores_codex":[0.7933064,0.1858864,0.004486526,0.003485674,0.01160074,0.001234249],"domain_scores_gemma":[0.866504,0.1084184,0.001682394,0.01964793,0.001779353,0.001968013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.00008899064,0.0004479795,0.002224856,0.0002199552,0.3647893,0.000232274,0.01340048,0.001124314,0.001966755,0.0113596,0.06032248,0.543823],"study_design_scores_gemma":[0.0002110195,0.0005388624,0.04404597,0.00003007308,0.3333858,0.00001588302,0.06408022,0.2267045,0.001564744,0.02309103,0.3048846,0.001447273],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2044533,0.01105825,0.7035809,0.05493037,0.0004729366,0.01038158,0.005073037,0.0002897192,0.009759957],"genre_scores_gemma":[0.4280109,0.0001440692,0.556002,0.0002450432,0.0002295196,0.000807239,0.000219,0.00005987978,0.01428239],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5423757,"threshold_uncertainty_score":0.9997803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.992173161325795,"score_gpt":0.7511059871365069,"score_spread":0.2410671741892881,"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."}}