{"id":"W3124450192","doi":"","title":"Eliciting Subjective Survival Curves: Lessons from Partial Identification","year":2015,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Life expectancy; Rounding; Construct (python library); Consistency (knowledge bases); Econometrics; Point (geometry); Inference; Parametric statistics; Mathematics; Expectancy theory; Identification (biology); Statistics; Psychology; Computer science; Social psychology; Artificial intelligence; Medicine; Discrete 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.048704,0.001617384,0.002186406,0.001944325,0.0008474797,0.004909574,0.002901417,0.003185356,0.006123817],"category_scores_gemma":[0.3245507,0.001299923,0.002391789,0.002601862,0.003922481,0.008442417,0.006168501,0.005439647,0.0009000547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001901945,"about_ca_system_score_gemma":0.001317404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003828388,"about_ca_topic_score_gemma":0.002140729,"domain_scores_codex":[0.9786897,0.01611542,0.001021733,0.001787908,0.001942178,0.0004429691],"domain_scores_gemma":[0.5663377,0.3744093,0.01267885,0.03894076,0.006303027,0.001330358],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003285637,0.0001679793,0.02462674,0.0005594757,0.0004220519,0.0003801191,0.003827047,0.2420135,0.000584743,0.6128345,0.00353245,0.1107229],"study_design_scores_gemma":[0.00003242522,0.00009267985,0.002981004,0.0001655503,0.00003743359,0.0001036409,0.0004027702,0.2980257,0.0006969789,0.6946859,0.002707563,0.00006829954],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03733607,0.0004580224,0.9546695,0.001572216,0.00004157778,0.0001050375,0.000540603,0.0002477946,0.005029257],"genre_scores_gemma":[0.7783163,0.001068104,0.2150678,0.0007664588,0.0001405173,0.0004644009,0.001459767,0.0002622877,0.002454503],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.951296,"threshold_uncertainty_score":0.2575744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09422028548523298,"score_gpt":0.4081399816353739,"score_spread":0.3139196961501409,"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."}}