{"id":"W4206388521","doi":"10.4095/329397","title":"A selection of earthquake scenarios for government planning purposes in 2021","year":2022,"lang":"en","type":"report","venue":"","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Selection (genetic algorithm); Government (linguistics); Computer science; Business; Construction engineering; Environmental planning; Engineering; Environmental 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":[],"consensus_categories":[],"category_scores_codex":[0.0008330895,0.0001860838,0.0004447896,0.000129226,0.0001620209,0.00002210101,0.0003665759,0.0001460694,0.0001758373],"category_scores_gemma":[0.0002197113,0.0001784493,0.000135249,0.0003218547,0.00003626572,0.0001026728,0.0003348947,0.0002913476,0.0000027016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002155345,"about_ca_system_score_gemma":0.0005068182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003076098,"about_ca_topic_score_gemma":0.0002820756,"domain_scores_codex":[0.9980608,0.00006433712,0.0004236745,0.0004646099,0.0006986934,0.0002878664],"domain_scores_gemma":[0.9990724,0.0002477587,0.0002736381,0.0002614535,0.0001176801,0.00002704531],"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":[0.0002716207,0.0009242147,0.1649956,0.001288415,0.001297348,0.0002516392,0.006084643,0.01926279,0.0001229487,0.007401338,0.3176589,0.4804405],"study_design_scores_gemma":[0.0009382487,0.001096216,0.1041971,0.0002495816,0.00006052462,0.000178019,0.0007464202,0.011634,0.0005194069,0.0006574799,0.8790082,0.0007148282],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1585231,0.01752829,0.3832913,0.005585761,0.02267134,0.008469446,0.000355945,0.0009181672,0.4026567],"genre_scores_gemma":[0.9248846,0.001304333,0.03165388,0.0004648147,0.0005585129,0.0009953192,0.00005750055,0.00005334204,0.04002775],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7663615,"threshold_uncertainty_score":0.727695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04154761142787985,"score_gpt":0.2926267819741239,"score_spread":0.2510791705462441,"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."}}