{"id":"W2094722085","doi":"10.1117/12.663109","title":"The Canadian Forces ILDS: a militarily fielded multisensor vehicle-mounted teleoperated landmine detection system","year":2006,"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":"Defence Research and Development Canada","funders":"Ministère de la Défense Nationale; Defence Research and Development Canada","keywords":"Teleoperation; Ground-penetrating radar; Detector; Computer science; Engineering; Real-time computing; Remote sensing; Simulation; Radar; Artificial intelligence; Aerospace engineering; Robot; Electrical engineering; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003684674,0.0002669358,0.0002922244,0.00007189104,0.0002783268,0.0001573048,0.0005683869,0.0001943068,0.000003257872],"category_scores_gemma":[0.0002088373,0.00019724,0.0003500131,0.0003820409,0.0001376943,0.0002140409,0.00004255257,0.0002801744,0.000003814866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002830436,"about_ca_system_score_gemma":0.00002630754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002626861,"about_ca_topic_score_gemma":0.0003079778,"domain_scores_codex":[0.9983879,2.790292e-8,0.0005556105,0.0002550336,0.0003762281,0.0004252372],"domain_scores_gemma":[0.9984382,0.00019864,0.0001262459,0.00006881044,0.001041224,0.0001268428],"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":[0.00003105015,0.00003469251,0.0001435799,0.0003319968,0.0002333922,9.214879e-8,0.00006744592,0.001405747,0.7963542,0.1991744,0.001455794,0.0007676047],"study_design_scores_gemma":[0.001251984,0.0002118391,0.00638833,0.0002880876,0.0001973384,0.00001725911,0.001691404,0.6388883,0.3348404,0.001252595,0.01437589,0.0005966116],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994963,0.0001048756,0.0001061462,0.000947558,0.0002415593,0.0005934775,0.00004562272,0.0001882763,0.002809493],"genre_scores_gemma":[0.9749373,0.00002434121,0.02405039,0.00002186531,0.0004175787,0.0002824489,0.000008391191,0.00004939332,0.0002082493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6374826,"threshold_uncertainty_score":0.8043215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007152127050761794,"score_gpt":0.2161654486148985,"score_spread":0.2090133215641367,"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."}}