{"id":"W4412813211","doi":"10.3397/nc_2025_0044","title":"From detection to resolution: a case-study of a comprehensive approach to managing mining noise impacts on communities","year":2025,"lang":"en","type":"article","venue":"NOISE-CON proceedings","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Soft dB (Canada)","funders":"","keywords":"Noise (video); Computer science; Environmental resource management; Resolution (logic); Environmental planning; Data mining; Environmental science; Data science; Remote sensing; Geography; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002687176,0.0002656934,0.0003803744,0.0006028125,0.0004833693,0.0003460984,0.0007082155,0.00007952367,0.000002572297],"category_scores_gemma":[0.00005200446,0.000267686,0.00005746976,0.001369964,0.00004066826,0.0004944184,0.0005745933,0.0002491791,0.000007631977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001303125,"about_ca_system_score_gemma":0.00005435731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001998503,"about_ca_topic_score_gemma":0.00008668657,"domain_scores_codex":[0.9983332,0.00003574357,0.0004185711,0.0005232517,0.0003166206,0.0003726314],"domain_scores_gemma":[0.9987714,0.000124551,0.0001859175,0.0003694718,0.0003950713,0.0001536142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0006608289,0.001800998,0.005251399,0.001069922,0.0003484808,0.000129488,0.8177847,0.003320612,0.05343068,0.002897044,0.01167316,0.1016327],"study_design_scores_gemma":[0.00461549,0.002883965,0.009802491,0.003206112,0.0002125915,0.0003870346,0.7281018,0.1971875,0.04598405,0.002182296,0.003732203,0.001704357],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.948792,0.00005131498,0.04096979,0.0006290003,0.0002347605,0.0006559873,0.000002395623,0.0002069697,0.008457793],"genre_scores_gemma":[0.9857667,0.0000013257,0.01136586,0.002586194,0.00008872533,0.0001012693,0.000001074975,0.00001619925,0.00007265148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1938669,"threshold_uncertainty_score":0.9999775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04087594808580323,"score_gpt":0.2777544080287832,"score_spread":0.23687845994298,"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."}}