{"id":"W2975248742","doi":"10.3390/w11102012","title":"Exploring an Alternative Configuration of the Hydroclimatic Modeling Chain, Based on the Notion of Asynchronous Objective Functions","year":2019,"lang":"en","type":"article","venue":"Water","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Université Laval","funders":"","keywords":"Pluvial; Environmental science; Climate model; Climatology; Forcing (mathematics); Calibration; Meteorology; Climate change; Computer science; Mathematics; Statistics; Geography; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002258118,0.0005142919,0.0004211531,0.0004861878,0.0003892193,0.001467971,0.001094326,0.000542014,0.001536384],"category_scores_gemma":[0.003164068,0.0002746628,0.0003736341,0.000568136,0.0005781463,0.002121387,0.001041712,0.0006919368,0.0001691454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007714414,"about_ca_system_score_gemma":0.0009166049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001915678,"about_ca_topic_score_gemma":0.002337402,"domain_scores_codex":[0.9991967,0.0003923625,0.00004599095,0.0001694844,0.0001296461,0.00006592154],"domain_scores_gemma":[0.9988353,0.0004222605,0.0002057266,0.0002200955,0.0002085351,0.0001082],"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":[0.00007581088,0.0000684229,0.002853023,0.0000353463,0.00004264309,0.00005352898,0.00005910185,0.9323441,0.001461455,0.04116742,0.0001958423,0.02164326],"study_design_scores_gemma":[0.00001454433,0.00006752479,0.0005131514,0.000008370582,0.00001143371,0.00001574119,0.00001848636,0.985419,0.0004928415,0.01291295,0.0005151235,0.00001087029],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1339189,0.0001010345,0.861654,0.0001784222,0.00002423495,0.00006834755,0.0001206057,0.0001142216,0.003820324],"genre_scores_gemma":[0.898163,0.0000774346,0.100679,0.00003499163,0.00001927805,0.00009882835,0.0001045325,0.00003689387,0.0007859969],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002258118,"threshold_uncertainty_score":0.01194221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0381344020764955,"score_gpt":0.2128502189977522,"score_spread":0.1747158169212567,"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."}}