{"id":"W1579843334","doi":"10.1002/hyp.9268","title":"Parameterization and multi‐criteria calibration of a distributed storm flow model applied to a Mediterranean agricultural catchment","year":2012,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Storm; Environmental science; Calibration; Hydrology (agriculture); Infiltration (HVAC); Drainage basin; Base flow; Hydrograph; Meteorology; Soil science; Mathematics; Geology; Statistics; Geotechnical engineering; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001372163,0.0001328178,0.0001719654,0.00001849287,0.0001091816,0.0000114976,0.00009372296,0.00007161716,0.00008818156],"category_scores_gemma":[0.00006606644,0.00008687454,0.00001490977,0.0001625088,0.0001545757,0.0002210412,0.0002057383,0.00005060372,0.00001338128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002458821,"about_ca_system_score_gemma":0.00000183708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001434349,"about_ca_topic_score_gemma":0.00002093572,"domain_scores_codex":[0.9991822,0.00002617605,0.0001819722,0.0002218396,0.0001377673,0.0002500151],"domain_scores_gemma":[0.9997248,0.00002828761,0.00006131659,0.00007684525,0.000007963255,0.0001007638],"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":[0.0008520307,0.00223757,0.1752121,0.0006629268,0.0001799445,0.000005201352,0.02785501,0.6539013,0.1283361,0.0003352048,0.0061124,0.004310137],"study_design_scores_gemma":[0.001792564,0.0007693326,0.1936215,0.00003709475,0.0002088401,0.00001037554,0.000599116,0.7745976,0.02457266,0.001871413,0.0009093684,0.001010069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9291018,0.00003645507,0.06951968,0.0006537869,0.00003804882,0.000335987,0.0000200826,0.00004798789,0.0002461991],"genre_scores_gemma":[0.9950607,0.00001993047,0.004286432,0.000397311,0.00002400327,0.0001021353,0.00008068721,0.000004057748,0.00002468032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1206963,"threshold_uncertainty_score":0.3542641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0303254660469065,"score_gpt":0.2495861478721152,"score_spread":0.2192606818252087,"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."}}