{"id":"W2137799418","doi":"10.1109/igarss.2008.4778815","title":"Incorporating Uncertainty in Uxo Discrimination","year":2008,"lang":"en","type":"article","venue":"","topic":"Control Systems and Identification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Unexploded ordnance; Curvature; Inversion (geology); Feature (linguistics); Context (archaeology); Representation (politics); Range (aeronautics); Computer science; Pattern recognition (psychology); Feature vector; Artificial intelligence; Domain (mathematical analysis); Data mining; Mathematics; Remote sensing; Geology; Engineering; Mathematical analysis","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":[0.00006918303,0.00003652923,0.00005174525,0.00005153547,0.00002198553,0.000008809308,0.0000285594,0.00001991395,0.00001586951],"category_scores_gemma":[0.00001175237,0.00003410642,0.00001149287,0.00009147261,0.000005389511,0.0001084021,0.000003602368,0.00003244083,0.00002871706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004842601,"about_ca_system_score_gemma":0.000004306469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003682499,"about_ca_topic_score_gemma":0.0009869605,"domain_scores_codex":[0.9997002,0.000007207827,0.0001296002,0.00005255526,0.00005284381,0.00005760333],"domain_scores_gemma":[0.9998873,0.000009148658,0.00001161523,0.00006548807,0.00001362012,0.00001277127],"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":[0.00001467255,0.0001148992,0.09121534,0.0002638728,0.00003522936,0.00003789602,0.005859944,0.5559494,0.195211,0.04131444,0.01223875,0.09774451],"study_design_scores_gemma":[0.0003470459,0.000006821853,0.1947232,0.00002156363,0.000001856669,0.000006836276,0.0002468168,0.8021766,0.0007959531,0.0005328759,0.001007772,0.0001326028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9709582,0.00006573571,0.007802365,0.00005744517,0.0001783955,0.000103583,6.222069e-7,0.0001373873,0.02069628],"genre_scores_gemma":[0.9993479,0.000006595092,0.0001062047,0.000005160499,0.00003703422,0.00001416657,0.00000721682,0.000005249122,0.0004705066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2462272,"threshold_uncertainty_score":0.139082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589846185505829,"score_gpt":0.204301492024798,"score_spread":0.1884030301697397,"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."}}