{"id":"W7117237560","doi":"10.23977/acss.2025.090409","title":"Deep Bayesian Modeling for Maritime Situational Awareness with Multisource and Heterogeneous Information","year":2025,"lang":"","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Situation awareness; Probabilistic logic; Bayesian network; Inference; Graphical model; Dynamic Bayesian network; Field (mathematics); Bayesian inference; Bayesian probability","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":[0.001387916,0.0009311927,0.0008616627,0.0008921203,0.0004092864,0.001121284,0.00159194,0.001035473,0.001475904],"category_scores_gemma":[0.004412398,0.0007643233,0.0009154145,0.001013149,0.0007298834,0.002752137,0.001712377,0.002567293,0.0003290005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001180398,"about_ca_system_score_gemma":0.001291166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01919306,"about_ca_topic_score_gemma":0.02184591,"domain_scores_codex":[0.9995461,0.000146415,0.00002279571,0.0001199838,0.0001072403,0.0000575078],"domain_scores_gemma":[0.9989558,0.000648874,0.0001222189,0.0000729084,0.0001433225,0.00005677246],"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":[0.00005303738,0.00002975499,0.0009804065,0.00004237313,0.00006043339,0.00003984237,0.00007251252,0.9430309,0.0008483974,0.0167154,0.001009221,0.03711767],"study_design_scores_gemma":[0.000001520067,0.000003171973,0.00008893283,0.000003666474,0.000004017953,0.000004069807,0.000003809927,0.990982,0.0001019392,0.008639624,0.0001640391,0.000003250249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009141057,0.0002955171,0.9889612,0.0003394361,0.00002750544,0.00001219752,0.0001408092,0.0002712684,0.0008111239],"genre_scores_gemma":[0.8316766,0.0009843167,0.1626213,0.0003022017,0.0001295644,0.0001131519,0.0009753155,0.0001511658,0.003046389],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01919306,"threshold_uncertainty_score":0.03816265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008069153614836492,"score_gpt":0.2406014818423183,"score_spread":0.2325323282274818,"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."}}