{"id":"W1570185147","doi":"","title":"Bayesian localization of multiple ocean acoustic sources with environmental uncertainties","year":2011,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Curse of dimensionality; Bayesian probability; Inversion (geology); Modal; Environmental noise; Noise (video); Variance (accounting); Random variable; Computer science; Environmental science; Acoustics; Mathematics; Statistics; Geology; Physics; Artificial intelligence; Seismology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00174822,0.0008277328,0.0009795718,0.001238473,0.0004489509,0.001301187,0.00126531,0.001295131,0.0009594091],"category_scores_gemma":[0.008170449,0.000866078,0.0004997072,0.001173554,0.001352504,0.002304849,0.001821805,0.0009665227,0.0003097721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001014165,"about_ca_system_score_gemma":0.001252518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007325988,"about_ca_topic_score_gemma":0.006411232,"domain_scores_codex":[0.9990643,0.0003162601,0.00004098571,0.0001819144,0.0003238817,0.00007272402],"domain_scores_gemma":[0.9980811,0.001265196,0.0002715004,0.00009500595,0.0002347971,0.00005243255],"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":[0.00005999831,0.00001531708,0.001075078,0.0000837934,0.00004513393,0.0001413109,0.0001146898,0.9138293,0.001864322,0.03388608,0.0006217191,0.0482632],"study_design_scores_gemma":[0.000009641731,0.00001063822,0.0003566936,0.0000221941,0.00001039516,0.00004410786,0.00002397995,0.9729043,0.0005388794,0.02525754,0.000803188,0.00001852225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006826779,0.0003355005,0.9916207,0.0001231498,0.00001141588,0.000008212183,0.00003324808,0.00008726094,0.0009537413],"genre_scores_gemma":[0.6330954,0.00194741,0.3595473,0.0001583823,0.0001697456,0.0001227311,0.0003450972,0.0001286313,0.004485295],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007325988,"threshold_uncertainty_score":0.01456666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01698039266318212,"score_gpt":0.1830281360022323,"score_spread":0.1660477433390502,"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."}}