{"id":"W3006839166","doi":"10.1109/taes.2020.2973866","title":"Airborne Maritime Surveillance Using Magnetic Anomaly Detection Signature","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Defence Research and Development Canada","funders":"","keywords":"Unexploded ordnance; Kinematics; Tracking (education); Computer science; Remote sensing; Anomaly detection; Explosive material; Radar tracker; Nonlinear system; Magnetic anomaly; Geodesy; Artificial intelligence; Geology; Radar; Geography; Geophysics; Physics; Telecommunications","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":[0.0002015821,0.0001912884,0.0002220596,0.00008692704,0.0002881297,0.0001660704,0.0001290337,0.0001418183,0.0002489368],"category_scores_gemma":[0.000004211225,0.0001760983,0.00005321236,0.0004119436,0.00006567007,0.0001217539,6.620015e-7,0.0005147139,0.00009173279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000381193,"about_ca_system_score_gemma":0.00009997305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00265666,"about_ca_topic_score_gemma":0.004852633,"domain_scores_codex":[0.9983634,0.0001464206,0.0001840452,0.0003967983,0.0003185302,0.0005908197],"domain_scores_gemma":[0.9994421,0.00009837897,0.00004318261,0.0001478678,0.00005064046,0.0002178494],"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":[0.0004659196,0.00005402784,0.003927682,0.0002574615,0.0001270822,0.00003329745,0.0004035074,0.9098762,0.05076698,0.000005970095,0.0001058866,0.03397598],"study_design_scores_gemma":[0.000542791,0.001136966,0.002336115,0.00002363626,0.00002957073,0.00008927013,0.0001611963,0.9901593,0.004385332,0.00001376598,0.0008274912,0.0002945328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3397392,0.002950249,0.6554282,0.0005201659,0.0003736805,0.0005218505,0.00008426925,0.0001257881,0.0002565693],"genre_scores_gemma":[0.9990533,0.0003086227,0.00008800325,0.0001094389,0.0001154069,0.000003954195,0.00000504278,0.00001237037,0.0003038478],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6593141,"threshold_uncertainty_score":0.7181081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01518590950406982,"score_gpt":0.2141318742544284,"score_spread":0.1989459647503585,"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."}}