{"id":"W4400100886","doi":"10.29173/iq1084","title":"Research Analysis: A World Data System and Canadian CoreTrustSeal Cohort Needs Assessment","year":2024,"lang":"en","type":"article","venue":"IASSIST Quarterly","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Science; Alliance de recherche numérique du Canada; U.S. Department of Energy","keywords":"Cohort; Data science; Geography; Medicine; Computer science; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.03255444,0.0005568322,0.000561605,0.02050546,0.009177038,0.004771079,0.002979754,0.0009408654,0.004220311],"category_scores_gemma":[0.04944916,0.0008583202,0.0006658226,0.03099171,0.001565354,0.002501829,0.004813573,0.001084605,0.0008199036],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09505648,"about_ca_system_score_gemma":0.2112208,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9811059,"about_ca_topic_score_gemma":0.9916294,"domain_scores_codex":[0.9809284,0.003068431,0.001852387,0.001524064,0.01000398,0.002622817],"domain_scores_gemma":[0.8829951,0.01031906,0.004697946,0.00519445,0.09148277,0.005310705],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004359198,0.0005011287,0.4948082,0.002071832,0.0001446965,0.001606205,0.1279684,0.001198967,0.002159859,0.01091742,0.1310194,0.227168],"study_design_scores_gemma":[0.00009482812,0.0002049608,0.6515516,0.001378583,0.000161281,0.0003144351,0.1156484,0.001726253,0.001769433,0.001176896,0.2257107,0.0002627601],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7734531,0.00203107,0.0108083,0.01262257,0.0001916433,0.01432519,0.1261438,0.0005409997,0.05988336],"genre_scores_gemma":[0.7943078,0.002478855,0.09352741,0.003737427,0.00009428509,0.01319883,0.07167587,0.0003453835,0.02063401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9970202,"threshold_uncertainty_score":0.6896863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05159392922084498,"score_gpt":0.3596360208189083,"score_spread":0.3080420915980633,"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."}}