{"id":"W7033006257","doi":"","title":"Optimisation de la prévision hydrologique d'ensemble par
\\nl'intégration de l'apprentissage profond dans une méthode
\\nmulti-modèle hybride","year":2024,"lang":"fr","type":"other","venue":"Espace École de technologie supérieure (École de technologie supérieure)","topic":"Science, Technology, and Education in Latin America","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drainage basin; Western europe; Bin","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009561185,0.001113224,0.001053448,0.0005309939,0.0003907005,0.001618355,0.001123283,0.001250917,0.003339985],"category_scores_gemma":[0.001691957,0.0006027105,0.00104973,0.0006226265,0.0004645718,0.001482958,0.001002614,0.001610467,0.0009640263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001033135,"about_ca_system_score_gemma":0.001941651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01928973,"about_ca_topic_score_gemma":0.02129667,"domain_scores_codex":[0.9996048,0.00006170601,0.00002491228,0.0001452491,0.0001086711,0.00005475208],"domain_scores_gemma":[0.9994525,0.0002047991,0.00004061728,0.00006413096,0.0002068598,0.00003106558],"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":[0.0001511345,0.00007466089,0.001986618,0.0001186028,0.000123727,0.000058621,0.00009132033,0.7678021,0.01513407,0.002350128,0.001833156,0.2102759],"study_design_scores_gemma":[0.000004957798,0.00001641108,0.0003360112,0.000006374104,0.000009849647,0.000008271279,0.000008892628,0.9953601,0.002947602,0.0004744602,0.0008207918,0.000006340286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04870027,0.0004363809,0.9457676,0.0002606056,0.0001323566,0.00004571383,0.0002038689,0.001899623,0.002553632],"genre_scores_gemma":[0.5366249,0.000602852,0.4463227,0.0002139607,0.0001164289,0.0001978201,0.0008723673,0.0006041274,0.01444485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01928973,"threshold_uncertainty_score":0.03835493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02067225657539396,"score_gpt":0.3077008625276708,"score_spread":0.2870286059522769,"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."}}