{"id":"W4409151076","doi":"10.1038/s41537-025-00560-x","title":"Enabling FAIR data stewardship in complex international multi-site studies: Data Operations for the Accelerating Medicines Partnership® Schizophrenia Program","year":2025,"lang":"en","type":"article","venue":"Schizophrenia","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Douglas College; Hotchkiss Brain Institute; École de Technologie Supérieure; University of Calgary","funders":"National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Health and Human Services; Government of Canada; National Institutes of Health; Canada Research Chairs; Wellcome Trust","keywords":"Computer science; Data quality; Interoperability; General partnership; Data governance; Data flow diagram; Workflow; Data management; Data science; Process management; Computer security; Data mining; World Wide Web; Database; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.2580838,0.0005577395,0.0006722253,0.003697635,0.005061103,0.01387119,0.004312265,0.002282752,0.004240516],"category_scores_gemma":[0.1855438,0.001024449,0.001799141,0.005065945,0.005887967,0.01556242,0.02726085,0.006588979,0.001317967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007371116,"about_ca_system_score_gemma":0.07614036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01080402,"about_ca_topic_score_gemma":0.01766878,"domain_scores_codex":[0.8780286,0.0909033,0.007584007,0.004583913,0.01551998,0.003380291],"domain_scores_gemma":[0.7314075,0.1204261,0.01694259,0.07271302,0.03445661,0.02405417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009564047,0.0007305263,0.03914577,0.002033655,0.0003047105,0.0008447352,0.01913869,0.003743802,0.003749478,0.1501214,0.1265432,0.6526877],"study_design_scores_gemma":[0.0006160124,0.0008924827,0.03360248,0.004481778,0.0002080346,0.0006619847,0.009866977,0.008749831,0.006794246,0.2232584,0.7104641,0.0004035973],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06329473,0.005554806,0.5562006,0.3054331,0.002195961,0.01073839,0.007102517,0.007312666,0.04216732],"genre_scores_gemma":[0.1176104,0.003430339,0.8499029,0.009804662,0.0008027146,0.0061078,0.005146914,0.001386102,0.005808106],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9956877,"threshold_uncertainty_score":0.9149148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5589192461860729,"score_gpt":0.5265233032922277,"score_spread":0.03239594289384518,"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."}}