{"id":"W4221116481","doi":"10.3390/su14053013","title":"Hybrid Differential Evolution-Based Regression Tree Model for Predicting Downstream Dam Hazard Potential","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Dam Engineering and Safety","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Differential evolution; Computer science; Data mining; Tree (set theory); Context (archaeology); Regression; Random forest; Regression analysis; Artificial intelligence; Machine learning; Statistics; Mathematics","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":[0.0003335511,0.0002424332,0.0002473673,0.0001192182,0.0004251151,0.00003031022,0.0002459968,0.00005565013,0.00004767298],"category_scores_gemma":[0.0002240234,0.000249075,0.0002198939,0.0001333291,0.00004486301,0.00009774583,0.0001091854,0.0003327061,6.838075e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001739836,"about_ca_system_score_gemma":0.0002552839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000244984,"about_ca_topic_score_gemma":0.000006688158,"domain_scores_codex":[0.9984239,0.00005302726,0.0003250374,0.0003607901,0.0003159794,0.000521212],"domain_scores_gemma":[0.99911,0.00007680397,0.00004038216,0.0004778724,0.0001773953,0.0001174799],"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":[0.0001210383,0.00009524573,0.001289293,0.0003312096,0.00002281161,0.000005584939,0.00009686865,0.9918295,0.00034166,0.0002569374,0.001011634,0.004598178],"study_design_scores_gemma":[0.0008820995,0.00007584961,0.003609205,0.000008677097,0.00003675773,0.000003533894,0.0001503833,0.990756,0.0002923937,0.00365403,0.0002779569,0.0002530573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4935755,0.00004685222,0.5044333,0.0001218212,0.0004806275,0.0004452086,0.0002114162,0.0006032065,0.00008205322],"genre_scores_gemma":[0.9980837,8.288282e-7,0.0008801208,0.000007063431,0.0001360647,0.0004119979,0.0001727824,0.00005271317,0.0002547932],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5045081,"threshold_uncertainty_score":0.9999961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005094179766378983,"score_gpt":0.2109653835564166,"score_spread":0.2058712037900376,"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."}}