{"id":"W2054999339","doi":"10.1109/tnn.2005.853337","title":"Connectionist-Based Dempster–Shafer Evidential Reasoning for Data Fusion","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Networks","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Dempster–Shafer theory; Computer science; Artificial intelligence; Evidential reasoning approach; Artificial neural network; Connectionism; Machine learning; A priori and a posteriori; Context (archaeology); Benchmark (surveying); Multilayer perceptron; Bayesian probability; Perceptron; Sensor fusion; Decision support system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002903669,0.0002038633,0.0001772297,0.00009118658,0.0005877712,0.0003194155,0.001002472,0.0001363616,0.00003056634],"category_scores_gemma":[0.000008255347,0.0001997385,0.0001135986,0.0002796039,0.00004095243,0.0007851737,0.000009131357,0.0003564451,0.00001850555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004745616,"about_ca_system_score_gemma":0.0000523257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003865954,"about_ca_topic_score_gemma":0.0001624522,"domain_scores_codex":[0.9983548,0.00008408277,0.0003027856,0.0006519695,0.0002203988,0.0003859698],"domain_scores_gemma":[0.9984652,0.0002479328,0.00008197842,0.0009757854,0.0000927258,0.0001363534],"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":[0.0000587654,0.00007747411,0.000002316626,0.000005685055,0.00001246344,0.000001652837,0.00002147924,0.7602395,0.0001130884,0.0002310135,0.001439129,0.2377974],"study_design_scores_gemma":[0.0005158801,0.0001421764,0.00000835028,0.00005386292,0.00003001061,0.00001525689,0.000002661613,0.9961,0.001100016,0.00006899955,0.00173503,0.0002277391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001863247,0.00009584798,0.9933997,0.002438965,0.001549355,0.0002532233,0.00001920871,0.0003411949,0.00003919552],"genre_scores_gemma":[0.9566434,0.00002227862,0.04107624,0.001654682,0.0003580714,0.00004864908,0.00001869079,0.00002037641,0.0001576302],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9547802,"threshold_uncertainty_score":0.81451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05764811737502774,"score_gpt":0.3007436376198504,"score_spread":0.2430955202448227,"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."}}