{"id":"W2129097250","doi":"10.3390/s120911638","title":"Accuracy Enhancement of Inertial Sensors Utilizing High Resolution Spectral Analysis","year":2012,"lang":"en","type":"article","venue":"Sensors","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Royal Military College of Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inertial navigation system; GPS/INS; Global Positioning System; Inertial measurement unit; Wavelet; Computer science; Inertial frame of reference; Noise (video); Engineering; Artificial intelligence; Assisted GPS; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001805005,0.0001713226,0.0002751502,0.0002387185,0.00005460794,0.00001116172,0.00007407091,0.0000982257,0.0001900413],"category_scores_gemma":[0.00005325689,0.0001705354,0.0001628362,0.0006934935,0.00003519915,0.0001697085,0.00001569671,0.0001397094,0.00005346835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000108811,"about_ca_system_score_gemma":0.000005320877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003064107,"about_ca_topic_score_gemma":0.00002689782,"domain_scores_codex":[0.9987367,0.00005322542,0.0003848129,0.0001393519,0.0002590891,0.0004267801],"domain_scores_gemma":[0.9994687,0.00006259082,0.00008082269,0.0002354155,0.00005359426,0.00009891512],"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":[0.00009651017,0.0001077734,0.006232194,0.00008863002,0.0007500276,0.000004301002,0.002095046,0.3450594,0.6402332,0.001556195,0.0003568448,0.003419888],"study_design_scores_gemma":[0.0003377387,0.00003870952,0.03088735,0.00002029399,0.0004330436,0.000003170874,0.0002312089,0.0995712,0.8670825,0.00002227757,0.001060791,0.0003117258],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956493,0.0002245325,0.0006236667,0.00002976737,0.0005630077,0.0001231356,0.0000118264,0.0001462415,0.002628566],"genre_scores_gemma":[0.9983931,0.00008281814,0.0008909355,0.000009188032,0.0004508529,0.000003466294,0.00005210979,0.00002453479,0.00009300073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2454882,"threshold_uncertainty_score":0.6954233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0132115080750597,"score_gpt":0.2448057049059137,"score_spread":0.2315941968308541,"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."}}