{"id":"W2985365311","doi":"","title":"Seismic Ambient Noise Tomography of Canada","year":2008,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Seismic Waves and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Seismic noise; Ambient noise level; Noise (video); Tomography; Geology; Seismic tomography; Seismology; Computer science; Sound (geography); Medicine; Radiology; Artificial intelligence; Oceanography","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":[0.0002064431,0.0004460087,0.0003583213,0.001300645,0.001740438,0.001483166,0.0006721091,0.0003844176,0.003687685],"category_scores_gemma":[0.0007302872,0.0002815859,0.0002108688,0.00355948,0.0003095383,0.000392886,0.0006536891,0.0006203836,0.0008051429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01122432,"about_ca_system_score_gemma":0.02104013,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9846213,"about_ca_topic_score_gemma":0.9918568,"domain_scores_codex":[0.9996506,0.000009915877,0.000006314569,0.00005851593,0.0001803803,0.00009424275],"domain_scores_gemma":[0.9994619,0.00001256086,0.00001320975,0.00001344191,0.000452486,0.00004631212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001656743,0.0003156821,0.4213006,0.0002928464,0.0002433607,0.001655801,0.003356586,0.1229147,0.1208735,0.01418741,0.06328338,0.2499194],"study_design_scores_gemma":[0.0001044781,0.00007887051,0.7679497,0.00009103699,0.0001288138,0.0002656816,0.001923632,0.1418669,0.01709196,0.001256374,0.06907278,0.0001698083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9003947,0.0006619968,0.007784081,0.001051742,0.000106402,0.0000661502,0.0216234,0.0008515814,0.0674601],"genre_scores_gemma":[0.9746295,0.0003636678,0.004091653,0.00007511081,0.00001797305,0.00001514047,0.00381272,0.0001449874,0.01684916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01537871,"threshold_uncertainty_score":0.08143848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01092542640304739,"score_gpt":0.1841979709573376,"score_spread":0.1732725445542902,"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."}}