{"id":"W2104957541","doi":"10.1109/icif.2002.1021171","title":"Voting fusion adaptation for landmine detection","year":2003,"lang":"en","type":"article","venue":"","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"General Dynamics (Canada)","funders":"","keywords":"Voting; Sensor fusion; Computer science; False alarm; Fusion; Constant false alarm rate; Heuristic; Scheme (mathematics); Artificial intelligence; Computer vision; Real-time computing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005287447,0.0000322118,0.00003344943,0.00001190919,0.00003649307,0.000006533161,0.00001236424,0.00001737817,0.0000141276],"category_scores_gemma":[0.00002943776,0.00002891741,0.00001788056,0.00006221156,0.000001847936,0.00002478706,0.000001132738,0.00002081285,0.00001221844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006779808,"about_ca_system_score_gemma":0.000001099736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003649146,"about_ca_topic_score_gemma":0.00001215909,"domain_scores_codex":[0.9998137,0.000004858647,0.00005292145,0.00004673481,0.00002229353,0.00005953503],"domain_scores_gemma":[0.9998797,0.00004592374,0.000005828859,0.00003672218,0.00001510263,0.00001671854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002270359,0.00001992514,0.0000244028,0.00003649725,0.000007172328,3.893141e-8,0.00006854764,0.01444369,0.5397117,0.05070586,0.0001097492,0.3948702],"study_design_scores_gemma":[0.0002895693,0.00003797072,0.001519873,0.000005246121,0.00001122344,0.00000101639,0.000106144,0.7666745,0.1915544,0.007484928,0.0321784,0.0001367691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09251583,0.000008835336,0.9034323,0.00001327802,0.00006353956,0.0001042349,7.181707e-7,0.0001197345,0.003741505],"genre_scores_gemma":[0.9076459,0.000001454477,0.09210742,0.000007781606,0.00003488146,0.00005205939,0.000001872963,0.000006515914,0.0001421152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8151301,"threshold_uncertainty_score":0.1179218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02284499109033452,"score_gpt":0.2503169798118112,"score_spread":0.2274719887214766,"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."}}