{"id":"W2805696881","doi":"10.3390/s18061872","title":"Satellite Launcher Navigation with One Versus Three IMUs: Sensor Positioning and Data Fusion Model Analysis","year":2018,"lang":"en","type":"article","venue":"Sensors","topic":"GNSS positioning and interference","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Defence Research and Development Canada; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Inertial measurement unit; Global Positioning System; Sensor fusion; Context (archaeology); Units of measurement; Inertial navigation system; Computer science; Filter (signal processing); Position (finance); Engineering; Computer vision; Orientation (vector space); Geography; Mathematics; 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":[0.0001002906,0.0001236853,0.0001486765,0.00009302027,0.0001143623,0.00007417319,0.000102603,0.00006192477,0.00002075881],"category_scores_gemma":[0.00001048955,0.00011562,0.00002115405,0.000281336,0.00007198789,0.0001792507,0.00004270849,0.0001130692,0.00003476897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003146243,"about_ca_system_score_gemma":0.000006432702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006452035,"about_ca_topic_score_gemma":0.0001789565,"domain_scores_codex":[0.9992703,0.00001771135,0.0001362472,0.0002617855,0.0001462354,0.0001677506],"domain_scores_gemma":[0.999381,0.00003555147,0.00002997711,0.0004122676,0.00008116671,0.00006003097],"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":[0.00086525,0.0001188657,0.007583934,0.0001953773,0.003135311,0.00002265457,0.007397206,0.8895583,0.06416782,0.001553427,0.0003788909,0.02502297],"study_design_scores_gemma":[0.0003055034,0.00008792894,0.003472999,0.00009013613,0.0003158842,0.000004716029,0.00008783773,0.9922068,0.003114445,0.00009714245,0.00004596794,0.0001706931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9644152,0.0000915138,0.03042075,0.00004512287,0.00006617112,0.00005983523,0.00004426124,0.0001744641,0.004682709],"genre_scores_gemma":[0.989166,0.00003886642,0.01032201,0.00001316934,0.0000828314,0.00000175545,0.0002783751,0.00002051807,0.00007644301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1026485,"threshold_uncertainty_score":0.4714849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04011042811310002,"score_gpt":0.2615783832741941,"score_spread":0.2214679551610941,"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."}}