{"id":"W2896722990","doi":"10.11575/prism/33197","title":"Sound Ecology and Acoustic Health, Part 2: An Android Application for Recording Noise Nuisances","year":2015,"lang":"en","type":"article","venue":"Open MIND","topic":"Noise Effects and Management","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Acoustics; Noise (video); Sound (geography); Android (operating system); Ecology; Computer science; Communication; Biology; Psychology; Artificial intelligence; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004088758,0.0008986566,0.0004418548,0.0006757591,0.0003523954,0.0007794868,0.0005760866,0.001272109,0.04603118],"category_scores_gemma":[0.001655337,0.0004184289,0.0003540076,0.0002337597,0.0002344383,0.0006634349,0.0007523843,0.0006749501,0.02366092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001082491,"about_ca_system_score_gemma":0.0002741853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000724192,"about_ca_topic_score_gemma":0.001304807,"domain_scores_codex":[0.999727,0.0000404492,0.00002789852,0.00005260107,0.0001226552,0.00002940408],"domain_scores_gemma":[0.999131,0.0004372112,0.00004231554,0.00006870142,0.0002137947,0.0001069858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001107536,0.0004579878,0.008031075,0.001831397,0.00005009883,0.002366792,0.001938517,0.0004725638,0.1080355,0.001826735,0.3601918,0.5136899],"study_design_scores_gemma":[0.0003770048,0.001472599,0.09453496,0.0008866997,0.0001722722,0.01110318,0.0005638561,0.01095117,0.03973243,0.001996285,0.8378345,0.0003749302],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1245951,0.01049811,0.4115345,0.008778852,0.00503016,0.008364264,0.02152975,0.2053152,0.2043541],"genre_scores_gemma":[0.3121594,0.006351032,0.3046167,0.01136537,0.00300056,0.007090539,0.01115116,0.01100551,0.3332597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04603118,"threshold_uncertainty_score":0.1539896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1749705426324326,"score_gpt":0.4859654912170399,"score_spread":0.3109949485846073,"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."}}