{"id":"W2148614910","doi":"10.1117/12.458390","title":"<title>Bayesian approach to sensor fusion in a multisensor land mine detection system</title>","year":2002,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"General Dynamics (Canada)","funders":"","keywords":"Bayesian probability; Sensor fusion; Bayesian inference; Inference; Computer science; Statistical inference; Data mining; Artificial intelligence; Fusion; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001330556,0.0003655776,0.0005675296,0.0005514002,0.0004252854,0.0009241175,0.0008445671,0.0008384243,0.00707548],"category_scores_gemma":[0.003071764,0.0002921996,0.0004349405,0.0009120982,0.0007591521,0.001295144,0.000591203,0.001027388,0.002076424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001440928,"about_ca_system_score_gemma":0.000864359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01154714,"about_ca_topic_score_gemma":0.0207989,"domain_scores_codex":[0.9990164,0.0002710957,0.00004190271,0.0001480145,0.0004686344,0.00005388687],"domain_scores_gemma":[0.9990315,0.0005157198,0.00005316979,0.00007566383,0.0002921351,0.00003188179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004185401,0.0001019971,0.001922088,0.0002385067,0.0001160619,0.0002386824,0.0002269596,0.2800839,0.01981917,0.1349442,0.02174301,0.5401469],"study_design_scores_gemma":[0.00001388993,0.00004806474,0.0008681042,0.0000286033,0.00002229982,0.000103108,0.00002168386,0.9351395,0.007960077,0.04172753,0.01402334,0.00004380177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003172287,0.0005707554,0.9913279,0.0007137001,0.0001166314,0.00002683234,0.00008991741,0.0003035132,0.003678504],"genre_scores_gemma":[0.2703729,0.002283089,0.6939585,0.0007396048,0.0004430719,0.0001497978,0.0005141408,0.0003907561,0.03114811],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01154714,"threshold_uncertainty_score":0.02366984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01238174388141854,"score_gpt":0.2174928732130266,"score_spread":0.205111129331608,"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."}}