{"id":"W2512605364","doi":"","title":"Bayesian Inversion of Time-difference-of-arrival Data to Localize Bowhead whales in the Chukchi Sea","year":2016,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Shell Exploration and Production Company","keywords":"Multilateration; Hydrophone; Whale; Inversion (geology); Geology; Computer science; Bayesian probability; Acoustics; Geodesy; Remote sensing; Oceanography; Seismology; Artificial intelligence; Physics","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":[0.0008548504,0.0003991472,0.0002577148,0.0006582531,0.0003070564,0.0005219197,0.0006589479,0.0004419852,0.0003986336],"category_scores_gemma":[0.004690666,0.0004163621,0.0003218585,0.0004701987,0.0003773812,0.0007317258,0.000810041,0.0005255505,0.0001810392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005717006,"about_ca_system_score_gemma":0.001540792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04963373,"about_ca_topic_score_gemma":0.05332194,"domain_scores_codex":[0.999754,0.00006701559,0.00001763543,0.00004957298,0.00007600469,0.00003568718],"domain_scores_gemma":[0.9994109,0.0002800013,0.00008035301,0.00005293241,0.0001482359,0.00002769267],"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":[0.00009532557,0.00005733698,0.01684995,0.00006772448,0.00007981904,0.000100022,0.0002232691,0.885399,0.01467145,0.004218098,0.0005141963,0.07772373],"study_design_scores_gemma":[0.000007914956,0.0000135243,0.003449381,0.000005070883,0.000007815279,0.00001550588,0.00002950944,0.9936839,0.001085306,0.00142188,0.0002672519,0.00001295805],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1940153,0.0001480147,0.8034946,0.0001528591,0.00002612229,0.00003784156,0.0002044182,0.0004206543,0.001500167],"genre_scores_gemma":[0.855074,0.0001156478,0.1435951,0.00004427375,0.00002195444,0.0000445403,0.0003731955,0.00005539114,0.000675871],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04963373,"threshold_uncertainty_score":0.09868968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0499774942452361,"score_gpt":0.2576682741456698,"score_spread":0.2076907799004337,"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."}}