{"id":"W2068778873","doi":"10.1121/1.4808895","title":"Quantifying ocean acoustic environmental sensitivity","year":2006,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; University of Victoria","funders":"","keywords":"Sonar; Sensitivity (control systems); Monte Carlo method; Range (aeronautics); Seabed; Gaussian; Underwater acoustics; Environmental science; Acoustics; Measure (data warehouse); Computer science; Geology; Underwater; Mathematics; Statistics; Physics; Oceanography; Data mining; Materials science; Engineering","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":[0.003685,0.0007329181,0.0004948447,0.001359898,0.0003027638,0.001261425,0.0005946766,0.0007659406,0.001354291],"category_scores_gemma":[0.03754811,0.0005208594,0.0003552079,0.001040058,0.0008248463,0.002210707,0.001853713,0.0006846622,0.0002661021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007234725,"about_ca_system_score_gemma":0.0005390705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002113612,"about_ca_topic_score_gemma":0.001375487,"domain_scores_codex":[0.9969212,0.0009128839,0.0001623501,0.0004543159,0.001355577,0.0001937137],"domain_scores_gemma":[0.9791221,0.01636933,0.001158286,0.001474914,0.001723278,0.0001520272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001117887,0.00004530641,0.0289725,0.0002116953,0.0001639838,0.0003017691,0.0001419843,0.9098715,0.01708743,0.006672743,0.0002602854,0.03615899],"study_design_scores_gemma":[0.00002198677,0.0002690914,0.07922021,0.0001117148,0.0001375319,0.0006202086,0.0003441986,0.8310664,0.05625908,0.02685017,0.004855172,0.0002442388],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5730478,0.0006556704,0.4093872,0.0004151531,0.0001143267,0.0001320115,0.001484504,0.0007090312,0.01405429],"genre_scores_gemma":[0.9872084,0.0002465117,0.01134433,0.00008170534,0.00003009368,0.00003703585,0.0005547206,0.00007296801,0.0004240999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003685,"threshold_uncertainty_score":0.01948833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02031270812808929,"score_gpt":0.2429499078272946,"score_spread":0.2226371996992053,"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."}}