{"id":"W4412592740","doi":"10.1016/b978-0-443-33631-7.00009-3","title":"Mining and refining hydroclimatic data for hybrid AI-driven sustainability models","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa; Université Laval","funders":"","keywords":"Refining (metallurgy); Sustainability; Environmental science; Computer science; Materials science; Ecology; Metallurgy","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008393443,0.0004727799,0.0006577239,0.00007206143,0.0003284765,0.00008787132,0.00085648,0.0002587555,0.0001378415],"category_scores_gemma":[0.0003626858,0.0004391331,0.0001163052,0.00001879174,0.0005207988,0.0001684201,0.002313405,0.0003876886,0.00001867456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003444393,"about_ca_system_score_gemma":0.000082947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004621556,"about_ca_topic_score_gemma":0.00004988686,"domain_scores_codex":[0.9972249,0.00004716828,0.0005835136,0.001278248,0.0003354235,0.0005307934],"domain_scores_gemma":[0.997732,0.000383325,0.0002625687,0.001428326,0.00003214074,0.0001615772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002317266,0.0000104005,0.00005313634,0.0003102709,0.00004439864,0.00002217534,0.0001444025,0.001785999,0.000008192163,0.0009378096,0.001130152,0.9955299],"study_design_scores_gemma":[0.0003174137,0.0001261051,0.000004756508,0.0005175766,0.0002347983,0.0000216384,0.000006805239,0.2178699,0.000005760564,0.113624,0.6666625,0.0006087064],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002888828,0.0001584081,0.00059579,0.0004096746,0.0001324797,0.0008287622,0.0002185575,0.0001351423,0.9946324],"genre_scores_gemma":[0.01731332,0.00001400904,0.01497024,0.0009564432,0.00008434126,0.00006875648,0.0002070518,0.00007961295,0.9663062],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9949212,"threshold_uncertainty_score":0.999806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04107137615215325,"score_gpt":0.2778556828384284,"score_spread":0.2367843066862752,"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."}}