{"id":"W2042155670","doi":"10.1121/1.4816556","title":"A practical weighting function for harbor porpoise underwater sound level measurements","year":2013,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Phocoena; Porpoise; Acoustics; Underwater; Noise (video); Weighting; Environmental science; Sound exposure; Amplitude; Range (aeronautics); Audiogram; Hydrophone; A-weighting; Sound (geography); Geology; Computer science; Physics; Oceanography; Audiology; Optics; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002108208,0.001007412,0.0004276883,0.001124126,0.0004607537,0.0008426716,0.0007746421,0.001098514,0.003639462],"category_scores_gemma":[0.006987343,0.0004232139,0.0004236507,0.001224766,0.0002937213,0.0007569166,0.0007760877,0.0005641018,0.002181882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005280353,"about_ca_system_score_gemma":0.0005929287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00148916,"about_ca_topic_score_gemma":0.002613702,"domain_scores_codex":[0.9988627,0.0003070973,0.00008244409,0.0001938335,0.0005008309,0.00005316396],"domain_scores_gemma":[0.9981085,0.0005963044,0.0001511035,0.0002231376,0.000870434,0.00005048596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000439237,0.0002594583,0.02148047,0.000601447,0.00007504537,0.0002837668,0.0003964715,0.01310911,0.2843864,0.005842202,0.007588546,0.6655377],"study_design_scores_gemma":[0.0001667591,0.00384365,0.1356103,0.0004983589,0.000374366,0.005140797,0.0007248207,0.3637619,0.3285936,0.01268619,0.1481059,0.0004934492],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06148808,0.0005086683,0.9300401,0.0001910128,0.0001923828,0.0003249894,0.0004761429,0.001976918,0.004801736],"genre_scores_gemma":[0.2089007,0.0004036998,0.785435,0.0001233257,0.00004448147,0.0005043777,0.000661317,0.000258622,0.003668537],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003639462,"threshold_uncertainty_score":0.0121752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07651665380921327,"score_gpt":0.2834129925710801,"score_spread":0.2068963387618668,"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."}}