{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007632569,0.0001471718,0.0001146593,0.0001252832,0.0001258773,0.00006727286,0.00007085813,0.0001002962,0.0001415305],"category_scores_gemma":[0.00001447076,0.0001447958,0.0000235483,0.00009231274,0.00006981392,0.00009374026,0.000003766068,0.000279381,0.000008916758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001216842,"about_ca_system_score_gemma":0.00004601805,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001022773,"about_ca_topic_score_gemma":0.03430058,"domain_scores_codex":[0.9992864,0.000005864185,0.0001166363,0.0001506893,0.0001407128,0.0002996998],"domain_scores_gemma":[0.9994338,0.00001649809,0.00001482828,0.0001491507,0.00001129922,0.000374483],"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":[0.000003872875,0.00001027101,0.01498541,0.00004568807,0.0000921933,0.00003173733,0.0003566006,0.6298019,0.3384179,0.000004993509,0.001097957,0.0151515],"study_design_scores_gemma":[0.0002689577,0.00002939993,0.03082073,0.00001835038,0.0002044464,0.00002922914,0.0003301413,0.9657635,0.0002818881,0.00001248089,0.001982965,0.0002579237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9451452,0.00006943473,0.05360961,0.00003824089,0.000223226,0.0001035331,0.00009722641,0.000117942,0.0005955803],"genre_scores_gemma":[0.9990984,0.00002385543,0.0004168341,0.0000519563,0.0001849393,0.000004703915,0.0000368873,0.00003789167,0.0001444976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.338136,"threshold_uncertainty_score":0.9833209,"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."}}