{"id":"W2468171748","doi":"10.1109/jsen.2016.2588981","title":"Novel Analog Ratio-Metric Optical Rotary Encoder for Avionic Applications","year":2016,"lang":"en","type":"article","venue":"IEEE Sensors Journal","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Thales Group; Canada Research Chairs; Government of Canada; Consortium de Recherche et d’innovation en Aérospatiale au Québec; Natural Sciences and Engineering Research Council of Canada; CMC Microsystems; Mitacs; Bombardier","keywords":"Avionics; Encoder; Computer science; Metric (unit); Electronic engineering; Engineering; Aerospace engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003908728,0.0005257715,0.0003232349,0.0005372907,0.0002181926,0.0005513214,0.001167344,0.0005533983,0.001745326],"category_scores_gemma":[0.0008337275,0.0002509388,0.0001917651,0.0004729908,0.0003119662,0.001108752,0.000458703,0.0003783882,0.000721712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003182483,"about_ca_system_score_gemma":0.0003613526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003502983,"about_ca_topic_score_gemma":0.0008219131,"domain_scores_codex":[0.9993607,0.00006532463,0.00003103901,0.0001162673,0.0003928811,0.0000337038],"domain_scores_gemma":[0.9994525,0.00009016254,0.0001178094,0.00005952973,0.0002411941,0.00003879333],"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":[0.0002396791,0.00006117085,0.001311281,0.0004495623,0.00002170486,0.0001716099,0.00008810131,0.001332399,0.7400814,0.006210477,0.003322707,0.2467098],"study_design_scores_gemma":[0.00007170178,0.00125042,0.003886937,0.00006087886,0.0001041669,0.003266001,0.00008352313,0.08687612,0.8398489,0.00127467,0.06312007,0.0001566758],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1102572,0.007754208,0.8602607,0.0006632737,0.001047449,0.0002384957,0.0002800083,0.002784796,0.01671396],"genre_scores_gemma":[0.629241,0.001809889,0.3586631,0.0004834291,0.0002939569,0.00008675604,0.0001701152,0.00006594331,0.009185732],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001745326,"threshold_uncertainty_score":0.005838633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03559185287339971,"score_gpt":0.2696494735821546,"score_spread":0.2340576207087549,"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."}}