{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003756694,0.0001131174,0.0002015118,0.0001581799,0.00002844135,0.00002390564,0.0001972403,0.00005104567,0.00003977956],"category_scores_gemma":[0.00006163819,0.00009944314,0.00005732263,0.0002006723,0.00003566566,0.0001235131,0.00003507987,0.00009967405,0.00005690174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001230169,"about_ca_system_score_gemma":0.00001136168,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01856963,"about_ca_topic_score_gemma":0.001825161,"domain_scores_codex":[0.998838,0.00006315985,0.0003054054,0.0002115306,0.0003274346,0.0002544888],"domain_scores_gemma":[0.9995348,0.00003583506,0.0001238012,0.0001487681,0.00001591141,0.0001408111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001930104,0.00002914367,0.9485991,0.000009702946,0.00001786454,0.00001555343,0.0002252749,0.04662125,0.0008696623,2.79235e-7,0.000026669,0.003566209],"study_design_scores_gemma":[0.0006757992,0.0001336464,0.9168355,0.0001542411,0.00004325623,0.000003723308,0.004252397,0.07491031,0.00243795,0.00006056182,0.0002563555,0.0002362261],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975097,0.0009447248,0.0001180974,0.00004556202,0.0003313848,0.00005072614,0.00002049125,0.000007613418,0.0009716527],"genre_scores_gemma":[0.9987341,0.00005586576,0.0008573354,0.00001583639,0.0001479544,3.92311e-7,0.00004000368,0.000003893777,0.0001446028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03176356,"threshold_uncertainty_score":0.9879658,"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."}}