{"id":"W2888418235","doi":"10.1108/afr-11-2017-0102","title":"Evaluating effectiveness of rainfall index insurance","year":2018,"lang":"en","type":"article","venue":"Agricultural Finance Review","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Crop insurance; Index (typography); Portfolio; Yield (engineering); Variance (accounting); Bootstrapping (finance); Basis risk; Precipitation; Crop yield; Econometrics; Economics; Statistics; Environmental science; Mathematics; Geography; Agriculture; Computer science; Meteorology; Agronomy; Finance","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":[0.0007587495,0.0002690981,0.0005649399,0.000006250078,0.0002431015,0.0000196132,0.0004875425,0.0001013998,0.0001597431],"category_scores_gemma":[0.0002617347,0.00007190846,0.0002332409,0.001143554,0.0001966199,0.0002646545,0.0001127655,0.0001568432,0.0001543343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003446649,"about_ca_system_score_gemma":0.00001209347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001361947,"about_ca_topic_score_gemma":0.00007846075,"domain_scores_codex":[0.9979438,0.0003253742,0.0004858485,0.0004480906,0.0004095612,0.000387382],"domain_scores_gemma":[0.9985882,0.0003634903,0.0003473968,0.0001029682,0.0005260113,0.00007191917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00006724554,0.0001347889,0.03372173,0.001510295,0.00003157087,0.000003743036,0.00006031995,0.00001158999,0.5701383,0.0005797881,0.001760538,0.3919801],"study_design_scores_gemma":[0.0001225546,0.0004689523,0.9771315,0.004912931,0.00002196862,0.00002801443,0.00002163831,0.000005974116,0.007748334,0.00009865875,0.009161224,0.0002782345],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9639832,0.03346701,0.000002173764,0.0003017581,0.000156511,0.0007357579,0.00002101637,0.00005492017,0.001277625],"genre_scores_gemma":[0.9702256,0.0288572,0.0001268407,0.0001539908,0.0002570332,0.00006314466,0.00003713,9.442239e-7,0.0002780512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9434098,"threshold_uncertainty_score":0.2932342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02901180822853029,"score_gpt":0.3066532307463834,"score_spread":0.2776414225178531,"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."}}