{"id":"W2017069111","doi":"10.1109/oceans.2014.7003266","title":"Passive energy based acoustic signal analysis for diver detection","year":2014,"lang":"en","type":"article","venue":"","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Energy (signal processing); SIGNAL (programming language); Spectral density; Detector; Acoustics; Computer science; Detection theory; Signal processing; Time–frequency analysis; Bioacoustics; Telecommunications; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002821468,0.0006566422,0.0005080592,0.0005446902,0.0002192306,0.0004810801,0.0004825626,0.0005080475,0.00126203],"category_scores_gemma":[0.0009663689,0.000205317,0.0002795583,0.000420112,0.0003628527,0.0007071182,0.0006083951,0.0004422044,0.0005808201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001644046,"about_ca_system_score_gemma":0.0001964434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002058162,"about_ca_topic_score_gemma":0.0002724015,"domain_scores_codex":[0.9997044,0.00007251857,0.000009959334,0.0000492509,0.0001484502,0.00001527425],"domain_scores_gemma":[0.999647,0.0001840151,0.0000328979,0.00004038006,0.00008417854,0.00001151752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003468287,0.0001031624,0.00143387,0.0003301696,0.00004881977,0.0002491742,0.000118118,0.05952361,0.6242388,0.005804927,0.001229195,0.3065734],"study_design_scores_gemma":[0.00001498232,0.0003751704,0.00337756,0.00003114725,0.00002695154,0.0006817557,0.0000579116,0.9028537,0.08203118,0.005899713,0.004600309,0.00004953489],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02739091,0.0003052281,0.9708076,0.00005312569,0.00003828435,0.00002871409,0.00004441922,0.0003526839,0.0009790208],"genre_scores_gemma":[0.5589492,0.0008806683,0.4348343,0.0001059005,0.0001502018,0.0001830376,0.0002515601,0.0001200449,0.004525139],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00126203,"threshold_uncertainty_score":0.004221916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007642119046198249,"score_gpt":0.2010356502740737,"score_spread":0.1933935312278754,"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."}}