{"id":"W4404535576","doi":"10.1121/10.0030475","title":"Range versus frequency averaging of underwater propagation loss for soundscape modeling","year":2024,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Defence Research and Development Canada","keywords":"Acoustics; Range (aeronautics); Transmission loss; Underwater; Octave (electronics); Broadband; Smoothing; Sound propagation; Computer science; Geology; Engineering; Mathematics; Telecommunications; Physics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001020772,0.0001079625,0.000226068,0.00003518058,0.0001631402,0.00004546871,0.0005306146,0.0000543181,0.0001554493],"category_scores_gemma":[0.0001240296,0.0000529283,0.000327028,0.0002622762,0.0004162634,0.000160665,0.00003986417,0.0003634357,0.00000540112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002690611,"about_ca_system_score_gemma":0.0001870856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002209337,"about_ca_topic_score_gemma":0.000006281429,"domain_scores_codex":[0.9984438,0.0001156299,0.0004257452,0.00009745072,0.0006467856,0.0002706182],"domain_scores_gemma":[0.9982907,0.001066258,0.0001644917,0.0001703875,0.0002420792,0.00006606957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003741503,0.00002931792,0.0004358911,0.0003058339,0.0002880465,0.000001501831,0.001705585,0.9788401,0.006662006,0.000004631088,0.001191132,0.01016181],"study_design_scores_gemma":[0.0003320088,0.0002923872,0.00008104012,0.00009466832,0.0001989616,0.00001985304,0.0009530273,0.9914353,0.0005808733,0.005877646,0.00006762557,0.00006660428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03302976,0.0005913868,0.9629644,0.002671522,0.0003654486,0.0001917884,0.00003682775,0.000008488818,0.0001403921],"genre_scores_gemma":[0.9655697,0.0002940573,0.03379093,0.0001018785,0.0001956384,4.159767e-7,0.00000241464,0.000007617432,0.00003729676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.93254,"threshold_uncertainty_score":0.2158353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.034337324625674,"score_gpt":0.2765127692378495,"score_spread":0.2421754446121754,"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."}}