{"id":"W2922973825","doi":"10.1017/asb.2019.5","title":"INDEX INSURANCE DESIGN","year":2019,"lang":"en","type":"article","venue":"Astin Bulletin","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo; Nanyang Technological University","keywords":"Indemnity; Index (typography); Basis risk; Insurance policy; Actuarial science; Uniqueness; Monotonic function; Function (biology); Mathematical optimization; Econometrics; Computer science; Mathematics; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.002949518,0.0006195407,0.0008494254,0.0006738793,0.0004643852,0.001734136,0.001548104,0.001485788,0.005857014],"category_scores_gemma":[0.00691218,0.000399448,0.0004492756,0.0005864153,0.0009142952,0.001892643,0.00130504,0.001101628,0.000559584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187293,"about_ca_system_score_gemma":0.001237112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005695536,"about_ca_topic_score_gemma":0.0003724331,"domain_scores_codex":[0.9979022,0.0008300593,0.0001067184,0.0004110064,0.0005205855,0.0002295493],"domain_scores_gemma":[0.9979262,0.0008663714,0.0003992797,0.0002823481,0.0003627922,0.0001629423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002580081,0.000226632,0.003802228,0.0003782687,0.0001165284,0.0003540943,0.0001640919,0.4750896,0.009888474,0.3563558,0.006256565,0.1471096],"study_design_scores_gemma":[0.00005218493,0.0002043043,0.0007449857,0.0000571278,0.00003480625,0.0002320442,0.00004898068,0.8823178,0.002530747,0.1063157,0.007438949,0.00002248075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04081918,0.0007742853,0.9397324,0.0007316647,0.00009138083,0.0001769254,0.0001594966,0.0001408901,0.01737367],"genre_scores_gemma":[0.8870518,0.0006459525,0.1032145,0.0001645496,0.0001049005,0.0001671245,0.0001372133,0.00005444304,0.008459467],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005857014,"threshold_uncertainty_score":0.01959372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00909297331177362,"score_gpt":0.176805861729796,"score_spread":0.1677128884180223,"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."}}