{"id":"W1484477319","doi":"","title":"Bayesian Acoustic Source Tracking and Track Prediction with Environmental Uncertainty","year":2010,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Flow Measurement and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Track (disk drive); Tracking (education); Bayesian probability; Computer science; Source tracking; Environmental science; Dynamic Bayesian network; Artificial intelligence; Acoustics; Data mining; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003989621,0.0009895264,0.00195144,0.001329753,0.0008720331,0.001798444,0.002325106,0.002324766,0.001703117],"category_scores_gemma":[0.01902531,0.002028987,0.001016793,0.001901172,0.001410511,0.003322431,0.001830772,0.001868043,0.0006741186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00160254,"about_ca_system_score_gemma":0.002492528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04193155,"about_ca_topic_score_gemma":0.03520277,"domain_scores_codex":[0.9986958,0.0003515046,0.0000772162,0.0004087797,0.0003322702,0.0001344117],"domain_scores_gemma":[0.9914308,0.006715092,0.0004812231,0.0004604791,0.0007845712,0.0001278356],"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":[0.0001146402,0.000029972,0.001022164,0.00003071992,0.00004918678,0.00003494417,0.00005028876,0.9484619,0.0004123367,0.009424182,0.0007155693,0.03965398],"study_design_scores_gemma":[0.000007831649,0.000004509444,0.0002286365,0.000002659132,0.000007252727,0.000006302883,0.000002092843,0.9950676,0.0001322963,0.004415452,0.0001196873,0.000005665602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01949485,0.0002387188,0.97869,0.0002166255,0.0000446161,0.00001709065,0.0001248637,0.0002371549,0.0009361698],"genre_scores_gemma":[0.7465522,0.0006497811,0.2398894,0.0001631766,0.0002264504,0.0001472266,0.001113008,0.0001808305,0.01107785],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04193155,"threshold_uncertainty_score":0.08337492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004181541557424695,"score_gpt":0.1497523042753225,"score_spread":0.1455707627178978,"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."}}