{"id":"W4410241996","doi":"10.18280/mmep.120407","title":"Flow Series Generation from Water Depth Data Using Statistical and Machine Learning Models: The Tocache Station Case","year":2025,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Series (stratigraphy); Computer science; Flow (mathematics); Machine learning; Artificial intelligence; Geology; Mathematics; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004786865,0.000149943,0.0001545577,0.0000197111,0.0002630226,0.0001319665,0.000102705,0.00006886604,0.00003390821],"category_scores_gemma":[0.00006740717,0.00009268212,0.00001055632,0.00006228183,0.00009174131,0.0002300487,0.0002794658,0.00022794,0.000004854917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002903454,"about_ca_system_score_gemma":0.00000300324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003787223,"about_ca_topic_score_gemma":0.00002993496,"domain_scores_codex":[0.9990375,0.00004686248,0.0002359662,0.000330053,0.0001243297,0.0002253076],"domain_scores_gemma":[0.9995466,0.0001522672,0.00002183932,0.0002125249,0.000006094101,0.00006066561],"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":[0.000004254691,0.00001343022,0.00002494548,0.00004180613,0.00001285893,0.00001137966,0.0006646088,0.9953939,0.001074825,0.001282651,0.000007911322,0.001467431],"study_design_scores_gemma":[0.00009670216,0.00002012242,0.000002267677,0.00004717084,0.00004547014,0.00008099911,0.00001376126,0.9757642,0.0001114829,0.02360546,0.00009591303,0.0001164098],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3341672,0.00007800879,0.665393,0.0001198371,0.00002192545,0.0001007058,0.00001364436,0.00005293336,0.00005276122],"genre_scores_gemma":[0.7857441,0.00001788416,0.2140672,0.00002141935,0.00001848903,0.000008012027,0.00006367631,0.00001337854,0.00004580393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4515769,"threshold_uncertainty_score":0.3779467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1161677332016745,"score_gpt":0.2429766740980182,"score_spread":0.1268089408963437,"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."}}