{"id":"W4411829293","doi":"10.1201/9781003642428-51","title":"Empowering Large Dams for the Future by Using Generative Artifical Intelligence ()","year":2025,"lang":"en","type":"book-chapter","venue":"","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tetra Tech (Canada)","funders":"","keywords":"Generative grammar; Environmental science; Computer science; Artificial intelligence","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":[0.0002768835,0.0003364964,0.0003028304,0.0000819979,0.0001338417,0.00008473819,0.0002507616,0.0003389743,0.0002490919],"category_scores_gemma":[0.00002867266,0.0002534041,0.0001800141,0.00004652988,0.00002202269,0.00005541679,0.00004951922,0.0004357363,0.000008110163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008374832,"about_ca_system_score_gemma":0.00002170807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001288751,"about_ca_topic_score_gemma":0.000004779266,"domain_scores_codex":[0.9989716,0.000009917781,0.0003369914,0.0002590167,0.0001567917,0.0002657251],"domain_scores_gemma":[0.9990796,0.0003736292,0.00003203022,0.0003842565,0.00007019106,0.00006024227],"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":[0.000005185508,0.000002639636,4.697718e-7,0.0001099096,0.0001463482,0.000001018064,0.00008769513,0.9228988,0.0002716142,0.0541676,0.01053063,0.01177808],"study_design_scores_gemma":[0.0000434633,0.000004989118,1.305465e-7,0.00004484056,0.00002593963,5.428755e-7,0.000020298,0.5762987,0.0007993485,0.0007349879,0.4218504,0.0001763907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.00001658573,0.006127237,0.9500955,0.00007747564,0.001482027,0.0003624393,0.0001082398,0.0002711902,0.04145936],"genre_scores_gemma":[0.003178428,0.001949843,0.1657512,0.0001958661,0.002494161,0.00009111322,0.0002113728,0.000305126,0.8258229],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7843635,"threshold_uncertainty_score":0.9999918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03484540264998329,"score_gpt":0.3345804964495842,"score_spread":0.2997350937996009,"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."}}