{"id":"W3166476367","doi":"10.5194/egusphere-egu21-10981","title":"Multi-year prediction of drought and heat stress to support decision making in the wheat sector","year":2021,"lang":"en","type":"article","venue":"","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ouranos","funders":"","keywords":"Climatology; Environmental science; Proxy (statistics); Climate change; Index (typography); Heat stress; Evapotranspiration; Forecast skill; Probabilistic logic; Heat wave; Meteorology; Econometrics; Environmental resource management; Geography; Computer science; Atmospheric sciences; Mathematics; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.001061687,0.000327898,0.0002959289,0.000475384,0.0001609807,0.0006455941,0.000262804,0.0004334346,0.000876084],"category_scores_gemma":[0.002031851,0.0001418784,0.0002859794,0.0005338531,0.0001021047,0.0005980007,0.0004179383,0.0005047806,0.0001690619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003472526,"about_ca_system_score_gemma":0.0005031751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01510565,"about_ca_topic_score_gemma":0.01420673,"domain_scores_codex":[0.999867,0.00004630421,0.00001328396,0.00003352713,0.00001871948,0.0000212279],"domain_scores_gemma":[0.9993562,0.0002659257,0.0001069541,0.00006691211,0.0001162466,0.00008770872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001657966,0.000095443,0.06000955,0.00003553841,0.00008736685,0.00005447947,0.00003831885,0.9142829,0.002139799,0.0007517791,0.002025269,0.02031379],"study_design_scores_gemma":[0.000006981825,0.00001361161,0.01493801,0.000004921631,0.000007010067,0.000003544255,0.00002008225,0.9837558,0.0004631624,0.0003705588,0.0004086757,0.000007611759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9651415,0.0002972357,0.02631612,0.0006846086,0.0001297489,0.00002497619,0.004612477,0.000578849,0.002214447],"genre_scores_gemma":[0.9925656,0.00007594914,0.005481875,0.00002465303,0.0000230869,0.000009402507,0.001572985,0.00001538729,0.0002309307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01510565,"threshold_uncertainty_score":0.0300355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01503071820006379,"score_gpt":0.2582198276438342,"score_spread":0.2431891094437704,"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."}}