{"id":"W2555639935","doi":"10.1109/joe.2016.2615686","title":"Striation Processing of Data From the 2013 Target and Reverberation Experiment (TREX13)","year":2016,"lang":"en","type":"article","venue":"IEEE Journal of Oceanic Engineering","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Naval Research Global; Defence Research and Development Canada; Pennsylvania State University","keywords":"Marine mammals and sonar; Sonar; Clutter; Reverberation; Signal processing; Spectrogram; Sonar signal processing; Computer science; Acoustics; Radar; Synthetic aperture sonar; Artificial intelligence; Computer vision; SIGNAL (programming language); Doppler effect; Image processing; Physics; Telecommunications; Image (mathematics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004943181,0.000396145,0.0004971016,0.0008290696,0.0003499498,0.0003944201,0.0003885599,0.0003334618,0.001446364],"category_scores_gemma":[0.0008093616,0.0001566316,0.0004238841,0.0007893212,0.0002396786,0.0002791625,0.0003997011,0.0005760289,0.0005330433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002160549,"about_ca_system_score_gemma":0.0004191735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004861861,"about_ca_topic_score_gemma":0.01579816,"domain_scores_codex":[0.999769,0.00001976108,0.00001004641,0.00005615891,0.0001116174,0.00003341628],"domain_scores_gemma":[0.9995456,0.00008202676,0.00005675979,0.00006860682,0.0001958116,0.00005119093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002239497,0.001237895,0.08239206,0.0002443334,0.0002814621,0.0008711239,0.0007610935,0.02978876,0.6722047,0.00122529,0.005303411,0.2034505],"study_design_scores_gemma":[0.00009527377,0.001287231,0.7736196,0.00001911296,0.0001013842,0.0006637535,0.0004254805,0.08237571,0.1317774,0.0006337157,0.008840195,0.0001611811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9514723,0.00006784842,0.03974112,0.0001047395,0.00008942789,0.0001220149,0.003323378,0.001117938,0.003961212],"genre_scores_gemma":[0.9334307,0.0001012951,0.0528358,0.00008575611,0.00003398084,0.000147689,0.00951202,0.0002783274,0.003574387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004861861,"threshold_uncertainty_score":0.009667099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04287977390490199,"score_gpt":0.2646429354167546,"score_spread":0.2217631615118526,"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."}}