{"id":"W1494956565","doi":"10.1109/i2mtc.2015.7151272","title":"Adaptive drift calibration of accelerometers with direct velocity measurements","year":2015,"lang":"en","type":"article","venue":"","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa; Bruyère; Carleton University","funders":"","keywords":"Accelerometer; Calibration; Noise (video); Computer science; Global Positioning System; SIGNAL (programming language); Sampling (signal processing); Position (finance); Acoustics; Control theory (sociology); Artificial intelligence; Physics; Computer vision; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006975503,0.0007537865,0.0004378277,0.0009203834,0.0002849436,0.000503208,0.0008893671,0.0006854577,0.0007536949],"category_scores_gemma":[0.004181197,0.0003266462,0.0003704823,0.0008296362,0.0002626367,0.0005708702,0.0005647902,0.0005559028,0.0004502716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003348365,"about_ca_system_score_gemma":0.0004188098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002062315,"about_ca_topic_score_gemma":0.00213652,"domain_scores_codex":[0.998724,0.0001809849,0.00006822966,0.0002660989,0.0006903554,0.00007022184],"domain_scores_gemma":[0.9988346,0.0002229497,0.000181875,0.0001830261,0.000555714,0.00002195458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005254024,0.0001974331,0.01754828,0.0003195171,0.0001464266,0.0002462784,0.0003922594,0.0537941,0.2827409,0.001841806,0.001406868,0.6408408],"study_design_scores_gemma":[0.00008023431,0.0008787325,0.03619863,0.0001079347,0.0001124196,0.001263155,0.0001670376,0.5336685,0.4124099,0.001032922,0.01394847,0.0001320687],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.197734,0.0008961618,0.7969295,0.0001247013,0.0003830711,0.0001115041,0.00007343772,0.001731063,0.002016519],"genre_scores_gemma":[0.7670872,0.0004883636,0.228617,0.00008204785,0.00007757466,0.00006603659,0.0001567824,0.000112964,0.003312165],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002062315,"threshold_uncertainty_score":0.004100621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06244767597718924,"score_gpt":0.226674334046078,"score_spread":0.1642266580688887,"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."}}