{"id":"W2981951126","doi":"10.4095/226350","title":"Probabilistic method for seismic vulnerability ranking of canadian hydropower dams","year":2007,"lang":"en","type":"report","venue":"","topic":"Dam Engineering and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Hydropower; Vulnerability (computing); Probabilistic logic; Ranking (information retrieval); Vulnerability assessment; Environmental science; Computer science; Statistics; Econometrics; Geography; Mathematics; Engineering; Artificial intelligence; Computer security; Psychology; Social psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002627818,0.0004309315,0.0008154121,0.000899106,0.00004951484,0.0000188741,0.0002713456,0.0005649445,0.0002340801],"category_scores_gemma":[0.0004992605,0.0004208073,0.0003033072,0.0004815603,0.00003563334,0.00004363648,0.00002054653,0.0005111332,0.000006820851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009899196,"about_ca_system_score_gemma":0.0007687916,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08957063,"about_ca_topic_score_gemma":0.05090003,"domain_scores_codex":[0.997728,0.00002375591,0.0007938432,0.0003898098,0.0004184592,0.0006461085],"domain_scores_gemma":[0.9982972,0.0003548681,0.00007689813,0.000651813,0.0003442949,0.0002748997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001067809,0.000026833,0.00005623692,0.005693926,0.0003142264,0.000009758639,0.0001376385,0.917672,0.000153865,0.0004243753,0.04907648,0.02642392],"study_design_scores_gemma":[0.0002192548,0.00003133996,0.0001317892,0.0001972055,0.0001288355,0.0000323476,0.00001200033,0.2962765,0.0006497193,0.000365641,0.7013794,0.000575882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005309273,0.0005702008,0.6456777,0.00002828057,0.002758421,0.0009422906,0.0003728451,0.0004486776,0.3486707],"genre_scores_gemma":[0.7472649,0.0008216977,0.2102357,0.00008394141,0.001929172,0.0004267186,0.001478505,0.001028166,0.03673124],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.746734,"threshold_uncertainty_score":0.9998244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03311690517320991,"score_gpt":0.3120469138978341,"score_spread":0.2789300087246242,"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."}}