{"id":"W4361286552","doi":"10.1177/00811750231151949","title":"The Anatomy of Cohort Analysis: Decomposing Comparative Cohort Careers","year":2023,"lang":"en","type":"article","venue":"Sociological Methodology","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Cohort; Computer science; Econometrics; Data science; Psychology; Statistics; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01608039,0.0001805395,0.0008480446,0.0002422549,0.001142736,0.0000355811,0.0007173984,0.000299634,0.0000892501],"category_scores_gemma":[0.002178722,0.0001245637,0.0005057461,0.002274825,0.003547878,0.00005749377,0.0001846595,0.0003466847,0.00003724833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009646574,"about_ca_system_score_gemma":0.00006693268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001689235,"about_ca_topic_score_gemma":0.001288009,"domain_scores_codex":[0.9882541,0.009511598,0.0005653615,0.0004831257,0.0004993373,0.0006864698],"domain_scores_gemma":[0.9874512,0.01150406,0.0003320298,0.00036503,0.000240169,0.0001075016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002499144,0.0000241291,0.8849165,0.000004691488,0.002219977,0.000008189064,0.004764642,0.0004125719,0.00003892109,0.1057114,0.0008678921,0.001006047],"study_design_scores_gemma":[0.0001190519,0.00005436789,0.937479,0.000002615865,0.0006368095,2.221764e-7,0.01863046,0.0001406638,0.0000311017,0.03702976,0.00571942,0.0001565262],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9732528,0.0005574256,0.003761658,0.001540273,0.0007059588,0.000764647,0.00001505547,0.0002276039,0.01917461],"genre_scores_gemma":[0.9928074,0.001142242,0.005446654,0.0001640474,0.0001258359,0.0001169736,0.00002352071,0.000007017554,0.0001662381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06868163,"threshold_uncertainty_score":0.9991639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2088264576884719,"score_gpt":0.4864860578802014,"score_spread":0.2776596001917295,"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."}}