{"id":"W2752116363","doi":"10.1016/j.insmatheco.2017.08.008","title":"IME’s Editorial Board","year":2017,"lang":"en","type":"article","venue":"Insurance Mathematics and Economics","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of Toronto","funders":"","keywords":"Editorial board; State (computer science); Political science; Current (fluid); Library science; Computer science; Engineering; Algorithm; Electrical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0009519196,0.0001464174,0.000274281,0.00005104278,0.001290289,0.0007227936,0.0005340473,0.0001224367,0.00003108762],"category_scores_gemma":[0.0001571592,0.0001538437,0.00009208921,0.0000257211,0.0004977681,0.0004331455,0.0001279066,0.00011745,0.0000846793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004805242,"about_ca_system_score_gemma":0.00004777471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001151233,"about_ca_topic_score_gemma":0.002184338,"domain_scores_codex":[0.9989244,0.00001986643,0.0003078828,0.0002521135,0.0001599011,0.0003358466],"domain_scores_gemma":[0.9988208,0.00006562088,0.0003473975,0.000583726,0.00006582965,0.0001165742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002988068,0.000258745,0.2203181,0.0002031466,0.0001884478,0.000007471973,0.01307327,0.00004621819,0.00001367713,0.7218038,0.02344134,0.02061591],"study_design_scores_gemma":[0.001141841,0.00004535485,0.1384756,0.00007757703,0.0000484359,0.000001332398,0.002623342,0.0006821612,0.00003516265,0.1880793,0.6680576,0.0007323105],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8669601,0.00007399051,0.00007188808,0.0006840327,0.01708709,0.0002939934,0.00002927827,0.0000526998,0.1147469],"genre_scores_gemma":[0.985271,0.001851047,0.002399856,0.00007717563,0.009811131,0.00002014605,0.000001347682,0.00002113998,0.0005471194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6446163,"threshold_uncertainty_score":0.9923987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221510010821956,"score_gpt":0.2878713275554386,"score_spread":0.2656562274472191,"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."}}