{"id":"W6920587487","doi":"10.60825/fmjr-ze05","title":"Evaluating the performance of the MIRFEE classifier plugin for PAMGuard at differentiating between whale vocalizations and anthropogenic noise in the Salish Sea","year":2025,"lang":"en","type":"report","venue":"Fisheries and Oceans Canada / Pêches et Océans Canada - Publications","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Whale; Classifier (UML); Plug-in; Humpback whale; Metadata; Bioacoustics; Feature extraction; Audio signal; Training set","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":[0.002232005,0.001503042,0.0006577169,0.000711825,0.0003834614,0.000726499,0.0009071719,0.001060227,0.002204918],"category_scores_gemma":[0.004190951,0.000356062,0.0005154747,0.0002732195,0.0003016309,0.001208948,0.0008503287,0.0009839372,0.001811042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005257607,"about_ca_system_score_gemma":0.0007046208,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02075679,"about_ca_topic_score_gemma":0.0245587,"domain_scores_codex":[0.9992557,0.000108229,0.00004453384,0.0002765344,0.0001850022,0.0001299449],"domain_scores_gemma":[0.9985714,0.0007445243,0.00004817717,0.0001242363,0.0003900708,0.0001214931],"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":[0.004765515,0.002407831,0.08823366,0.000534014,0.0006601782,0.0004649516,0.0004062487,0.2030167,0.109396,0.0007097506,0.02243759,0.5669675],"study_design_scores_gemma":[0.00009840316,0.001275088,0.04102704,0.00004159771,0.0001097124,0.0002075107,0.0001727793,0.8964224,0.05737749,0.0002345668,0.002962404,0.00007098828],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9411079,0.0005611661,0.03917767,0.0002589852,0.0002559973,0.0002125358,0.002090572,0.01243961,0.00389557],"genre_scores_gemma":[0.9152558,0.0002201052,0.06252662,0.0002467371,0.00005770123,0.0002163112,0.01091364,0.0005928208,0.009970169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9792432,"threshold_uncertainty_score":0.04127192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07684921028978411,"score_gpt":0.3165224106984346,"score_spread":0.2396732004086505,"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."}}