{"id":"W4321599449","doi":"10.3390/s23052446","title":"Characterizing Ambient Seismic Noise in an Urban Park Environment","year":2023,"lang":"en","type":"article","venue":"Sensors","topic":"Seismic Waves and Analysis","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Seismometer; Passive seismic; Ambient noise level; Seismic noise; Seismology; Noise (video); Geology; Remote sensing; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001900429,0.0001044813,0.0001394082,0.0001512953,0.00007164585,0.00003786815,0.0001125359,0.00003925261,0.0007537398],"category_scores_gemma":[0.000006155344,0.00009126948,0.00005402965,0.0002885299,0.00003159865,0.00009418226,0.000009254577,0.00008827034,0.001723164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006128319,"about_ca_system_score_gemma":0.00000728039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001217393,"about_ca_topic_score_gemma":0.00015635,"domain_scores_codex":[0.9990047,0.00006388836,0.0001711672,0.0002666019,0.0001767269,0.0003169012],"domain_scores_gemma":[0.9996188,0.00003244222,0.00004071977,0.0001891802,0.000003096648,0.0001157035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001085779,0.00001688819,0.8933073,0.000006185546,0.000011869,0.000111388,0.0007737168,0.09829351,0.001009511,0.000003859462,0.0002292901,0.006225628],"study_design_scores_gemma":[0.00008502183,0.00003170263,0.7546133,0.000006446413,0.000006613053,0.000001504991,0.0006037286,0.2349763,0.00009968857,0.00004188019,0.009420301,0.0001134873],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986491,0.00003353849,0.000002253405,0.0005773618,0.0001201222,0.0000631573,0.00005488241,0.00004922208,0.0004504179],"genre_scores_gemma":[0.9980837,0.0001483691,0.00003903732,0.0004982864,0.00009543477,3.50581e-7,0.000301206,0.000004232526,0.0008294183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.138694,"threshold_uncertainty_score":0.9990541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01591541456006552,"score_gpt":0.2064134081294146,"score_spread":0.190497993569349,"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."}}