{"id":"W2079047681","doi":"10.3390/s140712399","title":"Wireless Displacement Sensing of Micromachined Spiral-Coil Actuator Using Resonant Frequency Tracking","year":2014,"lang":"en","type":"article","venue":"Sensors","topic":"Shape Memory Alloy Transformations","field":"Materials Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Universiti Teknologi Malaysia; British Columbia Knowledge Development Fund; Natural Sciences and Engineering Research Council of Canada; CMC Microsystems; Ministry of Education, India; Ministério da Ciência, Tecnologia e Inovação; Kementerian Sains, Teknologi dan Inovasi; Canada Research Chairs","keywords":"Electromagnetic coil; Miniaturization; Actuator; Microactuator; Acoustics; Displacement (psychology); Spiral (railway); Antenna (radio); Electrical engineering; Materials science; Capacitor; Engineering; Physics; Mechanical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006338359,0.0001928302,0.0002924685,0.0001095784,0.0002034141,0.00005272171,0.0001731109,0.00007234197,0.0001597871],"category_scores_gemma":[0.00009910588,0.0001736318,0.00009056018,0.000172594,0.0001257774,0.0002141345,0.00003087101,0.0001074177,0.00004820227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008472608,"about_ca_system_score_gemma":0.00005102346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002423966,"about_ca_topic_score_gemma":0.00007204163,"domain_scores_codex":[0.9983449,0.0001767731,0.0005046083,0.000277954,0.0003296175,0.0003661311],"domain_scores_gemma":[0.9991286,0.0001267995,0.0002090769,0.0003505941,0.00009498923,0.00008990277],"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":[0.00002067162,0.00003044462,0.0002502096,0.00005335093,0.000007794654,0.000004534214,0.001309519,0.0007351758,0.9946933,0.0002435648,0.000006541077,0.002644841],"study_design_scores_gemma":[0.0005193561,0.00005371001,0.001312759,0.0001627621,0.00004858935,0.00003573617,0.0002957401,0.05156081,0.9454203,0.0002008905,0.0001395806,0.0002497131],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925357,0.00001660041,0.006105241,0.00009727784,0.0003732033,0.0001941035,0.00002674373,0.00008284964,0.0005682495],"genre_scores_gemma":[0.9817261,0.000002555608,0.01804177,0.00007323648,0.0000843527,0.000001072985,0.000006194854,0.0000291997,0.00003549478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05082564,"threshold_uncertainty_score":0.7080501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02236218979105078,"score_gpt":0.265800163011268,"score_spread":0.2434379732202172,"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."}}