{"id":"W3009908933","doi":"","title":"Dense Strong Motion Seismograph Networks in Canada: Opportunities and Applications. (Invited)","year":2010,"lang":"en","type":"article","venue":"AGUFM","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Seismometer; Motion (physics); Geology; Seismology; Computer science; Geography; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006770281,0.0003496199,0.0002181643,0.001031666,0.001171114,0.001500672,0.0004857467,0.0005026665,0.01348541],"category_scores_gemma":[0.003135694,0.0001734657,0.0001402454,0.002504003,0.0007351909,0.0007286654,0.0009639284,0.0004659633,0.0009339435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008025717,"about_ca_system_score_gemma":0.02513003,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9375528,"about_ca_topic_score_gemma":0.9820878,"domain_scores_codex":[0.9997488,0.00002390808,0.000007286839,0.00002887839,0.00009513012,0.00009608804],"domain_scores_gemma":[0.9976727,0.0004241874,0.00006955511,0.00003907236,0.001279862,0.0005146018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001723265,0.00002726167,0.0356701,0.0006227175,0.00003913971,0.000403683,0.0013108,0.00350977,0.00119264,0.01032569,0.629737,0.3169888],"study_design_scores_gemma":[0.00003726929,0.00004576832,0.09611119,0.0003439423,0.0000670374,0.000235308,0.00553665,0.003880364,0.0006476673,0.004309773,0.8887403,0.00004468231],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2395173,0.09799294,0.0285147,0.2867483,0.01286486,0.0007020431,0.04279456,0.001937791,0.2889275],"genre_scores_gemma":[0.6512698,0.07443192,0.01318383,0.005384874,0.004862085,0.0001194419,0.007890907,0.000245086,0.2426119],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.06244725,"threshold_uncertainty_score":0.12563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01674207294962698,"score_gpt":0.2008549926423935,"score_spread":0.1841129196927666,"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."}}