{"id":"W4410480724","doi":"10.47989/ir30colis51895","title":"‘It's a wide cluster of noise’: experiencing and describing information from environmental sounds","year":2025,"lang":"en","type":"article","venue":"Information Research an international electronic journal","topic":"Noise Effects and Management","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Environmental noise; Noise (video); Computer science; Cluster (spacecraft); Speech recognition; Acoustics; Artificial intelligence; Sound (geography); Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002620665,0.0001012064,0.0001296066,0.0007493531,0.0007135894,0.000166586,0.0003199513,0.00008626167,0.0006093453],"category_scores_gemma":[0.0004682549,0.000090222,0.00004077758,0.0001521854,0.00008147645,0.005223531,0.0002436327,0.001054522,0.000069168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001024734,"about_ca_system_score_gemma":0.0005664605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000309927,"about_ca_topic_score_gemma":0.00006636894,"domain_scores_codex":[0.9975093,0.0003255988,0.0007689974,0.00008435769,0.0007723917,0.0005393785],"domain_scores_gemma":[0.9987673,0.0003821486,0.0002951746,0.0001455158,0.0003045905,0.0001053179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003750738,0.0004115596,0.0880157,0.0005430991,0.001339256,0.000006361764,0.191376,0.001981842,0.006032598,0.2344214,0.07306612,0.3990553],"study_design_scores_gemma":[0.006470776,0.000665301,0.05767107,0.0008662138,0.00003149116,0.0000171198,0.08901685,0.0356105,0.0007269691,0.02269792,0.7858708,0.0003550064],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9185295,0.0000710059,0.04917011,0.003404209,0.0005901661,0.0006420391,0.00003356351,0.00002298766,0.02753642],"genre_scores_gemma":[0.9963983,0.0004663083,0.0003175705,0.002175808,0.0001133983,0.00006541266,0.0001166899,0.000004644823,0.0003419074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7128047,"threshold_uncertainty_score":0.6671903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04087971969068459,"score_gpt":0.4175485589263572,"score_spread":0.3766688392356726,"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."}}