{"id":"W2016501896","doi":"10.1109/tim.2013.2279004","title":"Design and Development of a Low-Cost Multisensor Inertial Data Acquisition System for Sailing","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Inertial measurement unit; Compass; Global Positioning System; Inertial navigation system; Data acquisition; Engineering; Instrumentation (computer programming); Inertial frame of reference; Acceleration; Accelerometer; System of measurement; Computer science; Systems engineering; Aerospace engineering; Simulation; 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":[0.0005937399,0.000619927,0.0005915885,0.0007297617,0.0005039182,0.0006414745,0.001091913,0.0007639509,0.002809266],"category_scores_gemma":[0.0006326359,0.0004007597,0.0002831436,0.0003297149,0.0002599489,0.0007791997,0.0005376053,0.000645445,0.002036957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000349628,"about_ca_system_score_gemma":0.001027733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006809121,"about_ca_topic_score_gemma":0.00096325,"domain_scores_codex":[0.9994337,0.00004889522,0.00004095967,0.0001019787,0.0003312649,0.00004321013],"domain_scores_gemma":[0.9995048,0.00006139896,0.00006135376,0.00005122473,0.0002797403,0.00004146513],"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":[0.0002117217,0.0001735573,0.003303862,0.0007982581,0.00006127267,0.0004150911,0.0005218419,0.006109421,0.5793242,0.004172667,0.005124687,0.3997834],"study_design_scores_gemma":[0.0002304061,0.004144535,0.016217,0.0001765667,0.0001838991,0.002804756,0.0002377951,0.1418021,0.642881,0.001036633,0.1900719,0.0002134409],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03572378,0.0005169848,0.9526847,0.0003321679,0.000336106,0.0008011356,0.0002454148,0.003314,0.0060456],"genre_scores_gemma":[0.2770716,0.0004832261,0.7091164,0.000392018,0.000156187,0.0009612499,0.0006352426,0.000240028,0.01094395],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002809266,"threshold_uncertainty_score":0.009397924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06470835635933456,"score_gpt":0.2557061824357489,"score_spread":0.1909978260764144,"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."}}