{"id":"W2897591841","doi":"10.1038/s41598-018-33974-y","title":"Nonstationary Temperature-Duration-Frequency curves","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Climate variability and models","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Duration (music); Heat wave; Context (archaeology); Climate change; Teleconnection; Environmental science; Climatology; Scale (ratio); Intensity (physics); Climate model; Econometrics; Geography; Mathematics; Geology; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001289052,0.00009453119,0.00008610301,0.00003551329,0.0005232892,0.0001258271,0.0001263885,0.00004690253,0.008356516],"category_scores_gemma":[0.0002270051,0.00008202633,0.00004546554,0.0004471071,0.0008041708,0.0004820998,0.0001004357,0.00006649367,0.0008311447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007407205,"about_ca_system_score_gemma":0.00005194258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009968151,"about_ca_topic_score_gemma":0.0001774464,"domain_scores_codex":[0.9982679,0.00003887692,0.0003727387,0.0006156835,0.0004833748,0.000221354],"domain_scores_gemma":[0.9990115,0.00002593125,0.0001342575,0.0006791844,0.00005228973,0.00009680189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006205002,0.0002484216,0.0936548,0.00004912767,0.00001036305,0.0001363021,0.001200153,0.0001866393,0.4666085,0.000850363,0.4361295,0.0009197165],"study_design_scores_gemma":[0.0004609252,0.0002914418,0.1047657,0.0004400829,0.00009038659,0.001429177,0.0003129072,0.004170082,0.1029296,0.4734118,0.3099088,0.001788994],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9309881,0.0000591928,0.0001538632,0.0009774679,0.004446142,0.0003122761,0.000005088035,0.00008910004,0.06296874],"genre_scores_gemma":[0.9920856,0.000007940031,0.002303123,0.0003758937,0.00007362878,0.00002164523,0.00008285666,0.00000772434,0.005041621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4725614,"threshold_uncertainty_score":0.9999468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01385853074042773,"score_gpt":0.2473358962356327,"score_spread":0.233477365495205,"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."}}