{"id":"W4410226908","doi":"10.1109/joe.2025.3553955","title":"Directionality of Tonal Components of Ship Noise Using Arctic Hydrophone Array Elements","year":2025,"lang":"en","type":"article","venue":"IEEE Journal of Oceanic Engineering","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Ministère de la Défense Nationale","keywords":"Acoustics; Hydrophone; Noise (video); Underwater acoustics; Directionality; Computer science; Engineering; Geology; Underwater; Physics; Oceanography; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003111588,0.0002856712,0.0001172946,0.0007707807,0.0001769571,0.0003629004,0.0001425706,0.0001105231,0.001107221],"category_scores_gemma":[0.0009206157,0.0001786978,0.0001334495,0.0005077089,0.0001228512,0.0002165564,0.0003569688,0.000144502,0.000422246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003498339,"about_ca_system_score_gemma":0.000348514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02688338,"about_ca_topic_score_gemma":0.07943183,"domain_scores_codex":[0.99975,0.00003546664,0.00001215027,0.00006751439,0.0001054897,0.00002943371],"domain_scores_gemma":[0.9996352,0.00006468708,0.00003530552,0.00002213714,0.0002155344,0.00002704527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009353411,0.00004893696,0.4555797,0.0001439594,0.0001277875,0.0001230422,0.001449459,0.01519671,0.3710586,0.0006389989,0.0011893,0.1535082],"study_design_scores_gemma":[0.00002100836,0.0001433581,0.8921724,0.0000376963,0.0001018667,0.00020449,0.0006409801,0.03708049,0.06575858,0.0003078104,0.003466089,0.00006516884],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711879,0.00008694386,0.02071926,0.00003777467,0.00001408102,0.00002117731,0.001373037,0.0001728861,0.006386954],"genre_scores_gemma":[0.9835327,0.0001321695,0.01297828,0.0000193404,0.00000582689,0.00002027699,0.0009834355,0.00003764094,0.002290416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02688338,"threshold_uncertainty_score":0.0534538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02963092614308427,"score_gpt":0.2647513856028405,"score_spread":0.2351204594597562,"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."}}