{"id":"W3118349495","doi":"10.5194/gi-10-101-2021","title":"Magnetic interference mapping of four types of unmanned aircraft systems intended for aeromagnetic surveying","year":2021,"lang":"en","type":"article","venue":"Geoscientific instrumentation, methods and data systems","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"RES’EAU-WaterNET; Natural Sciences and Engineering Research Council of Canada","keywords":"Magnetometer; Interference (communication); Rotor (electric); Aeromagnetic survey; Acoustics; Earth's magnetic field; Fluxgate compass; Spacecraft; Magnetic field; Aerospace engineering; Physics; Geodesy; Electrical engineering; Engineering; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0001605405,0.0001986498,0.000154161,0.0006914997,0.0002646342,0.0001641733,0.0002229731,0.000167742,0.0005355758],"category_scores_gemma":[0.0005613032,0.00007311827,0.0001132573,0.0003162529,0.0001599374,0.0002067678,0.00023502,0.0001012516,0.00009816734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003061062,"about_ca_system_score_gemma":0.0001517629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002784409,"about_ca_topic_score_gemma":0.005463445,"domain_scores_codex":[0.9998361,0.00003041103,0.000008859275,0.00002660637,0.00006977744,0.00002828711],"domain_scores_gemma":[0.9995362,0.00008802965,0.00007033459,0.00003785679,0.000213808,0.00005394859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002794948,0.000433703,0.1172018,0.000292073,0.0001403331,0.0007902842,0.0007301898,0.03128535,0.7345968,0.0006666834,0.001052674,0.1100152],"study_design_scores_gemma":[0.00007110988,0.002822555,0.5953706,0.00001753987,0.00008891313,0.0005736499,0.0006108401,0.1327316,0.2642504,0.0003230956,0.003082621,0.00005703941],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965066,0.00002671885,0.002553083,0.000008264886,0.000005790061,0.0000237862,0.00007445588,0.00005062292,0.0007505601],"genre_scores_gemma":[0.9976692,0.00000980709,0.001928527,0.000004752971,0.000001056134,0.00001113712,0.0001151465,0.000004235108,0.0002560432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002784409,"threshold_uncertainty_score":0.005536437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09285785552788287,"score_gpt":0.3443518478258814,"score_spread":0.2514939922979985,"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."}}