{"id":"W3211138665","doi":"10.2139/ssrn.3946998","title":"Multi-Signal Approaches for Repeated Sampling Schemes in Inertial Sensor Calibration","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Calibration; SIGNAL (programming language); Sampling (signal processing); Computer science; Environmental science; Statistics; Mathematics; 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":[0.0004366116,0.0001287927,0.0001521132,0.00008831442,0.00009025812,0.00005325413,0.00006423634,0.000105892,0.00001041469],"category_scores_gemma":[0.00006333439,0.0001300693,0.00008302687,0.0002084151,0.00001051612,0.0001929667,0.000007994215,0.0007774588,0.000002003515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004543397,"about_ca_system_score_gemma":0.0002912042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001845961,"about_ca_topic_score_gemma":0.0005000724,"domain_scores_codex":[0.9984024,0.00004235976,0.0003135697,0.0001465681,0.0001165803,0.000978537],"domain_scores_gemma":[0.99974,0.00003546304,0.00004280994,0.00007653673,0.00006267642,0.00004251286],"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":[0.000188516,0.0001305934,0.00153671,0.00007535544,0.0002266718,0.00001466556,0.000563076,0.3084943,0.6297721,0.01270874,0.00003208143,0.04625724],"study_design_scores_gemma":[0.002148776,0.00008535117,0.0004621873,0.00004964697,0.00003587382,0.0002657397,0.0009935735,0.8668789,0.1232629,0.004901724,0.0005740777,0.0003412055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5535242,0.001209971,0.4447381,0.0001210826,0.0001556965,0.0001277034,0.000003538811,0.00007552537,0.0000441179],"genre_scores_gemma":[0.99321,0.0002871407,0.005817866,0.00001633851,0.0003988773,0.00001125961,0.00006213519,0.00003582268,0.0001605473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5583846,"threshold_uncertainty_score":0.5304071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03549875448906972,"score_gpt":0.2500681731539549,"score_spread":0.2145694186648851,"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."}}