{"id":"W7084097583","doi":"10.6084/m9.figshare.30215608.v1","title":"Additional file 2 of Leveraging multigenerational health data to enhance mental disorder risk prediction: a population-based cohort study","year":2025,"lang":"en","type":"article","venue":"Figshare","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Mental health; Cohort study; Cohort; Data collection; Risk assessment; MEDLINE","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002110254,0.0008914031,0.001116183,0.002007662,0.001254571,0.001376914,0.001725527,0.001312907,0.8164197],"category_scores_gemma":[0.03735179,0.0006058401,0.001442516,0.003811746,0.0002399834,0.001782806,0.001159805,0.001085179,0.09441224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008795862,"about_ca_system_score_gemma":0.001995631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01807883,"about_ca_topic_score_gemma":0.02572379,"domain_scores_codex":[0.9990712,0.0002425804,0.0002055552,0.0002347071,0.0001269317,0.0001189499],"domain_scores_gemma":[0.9744631,0.01905254,0.001720014,0.001660081,0.002407782,0.0006964857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0004125286,0.0001099527,0.008091968,0.00191911,0.00009573258,0.0001061639,0.0001060454,0.0003936049,0.00005436807,0.00111143,0.9792809,0.008318086],"study_design_scores_gemma":[0.01812911,0.0009013441,0.1455661,0.01086604,0.001335942,0.001730818,0.001669272,0.005089827,0.001090512,0.02489793,0.7883122,0.0004110035],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003926464,0.00002016334,0.0002708625,0.0001056671,0.00002196013,0.0001748938,0.9980586,0.00008068161,0.0008743564],"genre_scores_gemma":[0.02320372,0.000285994,0.006876168,0.001165613,0.0002112693,0.009152454,0.9402885,0.0005847786,0.01823162],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8164197,"threshold_uncertainty_score":0.2618549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08281626995568794,"score_gpt":0.2901878591047959,"score_spread":0.2073715891491079,"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."}}