{"id":"W2066301443","doi":"10.1121/1.2940581","title":"Bayesian geoacoustic inversion of ship noise on a horizontal array","year":2008,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Inversion (geology); Geology; Acoustics; Waves and shallow water; Bayesian probability; Stern; Underwater acoustics; Geodesy; Underwater; Seismology; Computer science; Oceanography; Physics; Artificial intelligence","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":[0.0005872034,0.0003292004,0.000282699,0.0002770023,0.0001377165,0.0003578971,0.0004050205,0.0003153702,0.0005187616],"category_scores_gemma":[0.002986494,0.0003051877,0.0002359405,0.0003402405,0.0003309197,0.0007623647,0.0006329767,0.000365528,0.0002270181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002412351,"about_ca_system_score_gemma":0.0007026132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007418753,"about_ca_topic_score_gemma":0.008762249,"domain_scores_codex":[0.9997097,0.00007615404,0.00001157188,0.00005390611,0.0001161711,0.00003249936],"domain_scores_gemma":[0.9995676,0.0002323098,0.00006232702,0.00003783935,0.00008610599,0.0000138127],"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":[0.0001069547,0.00002554982,0.003663123,0.00003279902,0.0000357977,0.0000461909,0.00006015352,0.9180773,0.01665324,0.003106037,0.0002127356,0.05798016],"study_design_scores_gemma":[0.000008631538,0.00001615899,0.001564236,0.000002998787,0.000004833932,0.000008378589,0.00001112202,0.9943928,0.002611673,0.001204554,0.0001678038,0.000006735083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3202519,0.00006881342,0.6774238,0.00008333367,0.00001595405,0.00001546337,0.0001199332,0.000219057,0.001801781],"genre_scores_gemma":[0.9198807,0.00008700288,0.07811477,0.0000328693,0.00001658496,0.00002239306,0.0002811183,0.0000400473,0.001524477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007418753,"threshold_uncertainty_score":0.01475114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0214505681720333,"score_gpt":0.2377565068066721,"score_spread":0.2163059386346388,"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."}}