{"id":"W2600706287","doi":"","title":"Stress Monitoring Potential of Ambient Noise Interferometry in Deep Mine Environments","year":2015,"lang":"en","type":"article","venue":"2015 AGU Fall Meeting","topic":"Seismic Waves and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Noise (video); Ambient noise level; Stress (linguistics); Interferometry; Environmental science; Geology; Remote sensing; Computer science; Optics; Artificial intelligence; Physics; Sound (geography)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002799322,0.000418494,0.0002746421,0.0005631821,0.0002036727,0.0005105637,0.0003287096,0.0003882032,0.0005833727],"category_scores_gemma":[0.0006923345,0.0001325863,0.0001469754,0.0004051597,0.0001487044,0.0005632476,0.000420269,0.0002229886,0.0001868939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009806704,"about_ca_system_score_gemma":0.0002022829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009818985,"about_ca_topic_score_gemma":0.003113623,"domain_scores_codex":[0.9998193,0.00004774933,0.000006522021,0.0000434819,0.00005364298,0.00002932622],"domain_scores_gemma":[0.9995919,0.0001029191,0.00004165595,0.0000234464,0.0001902161,0.00004989213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001471411,0.000477869,0.3949322,0.0002246231,0.0001729668,0.0004700212,0.0005253124,0.02402333,0.2516508,0.0009445257,0.001659498,0.3234475],"study_design_scores_gemma":[0.00008774441,0.001451789,0.6515813,0.00008643861,0.0004010022,0.0006147472,0.001005049,0.2998487,0.03922329,0.001952698,0.003662594,0.00008466946],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9772047,0.0002675303,0.01930552,0.000113766,0.0000359913,0.00001175703,0.0002507199,0.0001148794,0.002695167],"genre_scores_gemma":[0.9945978,0.0001031797,0.004829952,0.00002043435,0.00003291403,0.00000587941,0.00009806002,0.00001007439,0.0003016621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009818985,"threshold_uncertainty_score":0.00195241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01660024695016385,"score_gpt":0.2243467068046509,"score_spread":0.2077464598544871,"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."}}