{"id":"W1193441318","doi":"10.13140/rg.2.2.28923.72481","title":"Approches flexibles et optimales en analyse fréquentielle régionale des crues en se basant sur les fonctions de profondeur","year":2015,"lang":"fr","type":"article","venue":"EspaceINRS Institutional Digital Repository (Institut National de la Recherche Scientifique)","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Humanities; Philosophy; Political science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.007325409,0.0005793195,0.0004100726,0.0004434021,0.001546936,0.0008439349,0.0007469375,0.0008642647,0.0001445564],"category_scores_gemma":[0.00811231,0.0005846573,0.0003558614,0.001079291,0.006084352,0.003323613,0.0007519057,0.001161688,0.0003253508],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005756019,"about_ca_system_score_gemma":0.002913758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001038426,"about_ca_topic_score_gemma":0.0004873075,"domain_scores_codex":[0.9934448,0.00251515,0.0006684926,0.00108675,0.001420792,0.0008640073],"domain_scores_gemma":[0.996255,0.002117648,0.000251792,0.0003389956,0.0004779058,0.000558621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00037392,0.002847483,0.137204,0.0005173151,0.0009958702,0.0004626699,0.01295482,0.4699143,0.01033394,0.3132712,0.04493206,0.006192503],"study_design_scores_gemma":[0.002204656,0.000247482,0.08872893,0.00109299,0.0004154746,0.001302758,0.003457826,0.02787692,0.01486687,0.1551074,0.7028734,0.001825289],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3809356,0.006623875,0.09070652,0.01084443,0.001930937,0.001127753,0.000359933,0.0003657136,0.5071053],"genre_scores_gemma":[0.8296734,0.0008619725,0.0468052,0.0004198536,0.0003853523,0.0002504319,0.0001783217,0.00004202379,0.1213834],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6579413,"threshold_uncertainty_score":0.9997529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1346639295604377,"score_gpt":0.3350430603240541,"score_spread":0.2003791307636163,"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."}}