{"id":"W2796049108","doi":"10.1109/tcpmt.2018.2810738","title":"Packaging-Induced Range Tunability of Tactile Sensors for Physiological Signal Monitoring Applications","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Components Packaging and Manufacturing Technology","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta; CMC Microsystems","keywords":"Microelectromechanical systems; Emulation; Tactile sensor; Materials science; Polydimethylsiloxane; SIGNAL (programming language); Pressure sensor; Fabrication; Reusability; Sensitivity (control systems); Electronic engineering; Acoustics; Computer science; Optoelectronics; Mechanical engineering; Nanotechnology; 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":[0.00009617044,0.0002444754,0.0003429311,0.0002630235,0.0002708247,0.00001857538,0.0001571266,0.0001837896,0.00001204548],"category_scores_gemma":[0.000005442424,0.0002422951,0.00007249021,0.0001145392,0.0002036852,0.00008661301,0.000004929032,0.000227121,0.000006226419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005376652,"about_ca_system_score_gemma":0.000005137624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001506482,"about_ca_topic_score_gemma":0.000002398523,"domain_scores_codex":[0.9988628,0.00002373505,0.0003070495,0.0003496244,0.00009511043,0.0003616903],"domain_scores_gemma":[0.9993542,0.0001196794,0.0000676026,0.0003340119,0.00005227203,0.00007218105],"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":[0.0000545851,0.00008917288,0.00008224969,0.0001798811,0.0000784216,0.000001133218,0.00008135592,0.01634668,0.9605725,0.00004108712,0.000008610305,0.02246429],"study_design_scores_gemma":[0.0004520256,0.0001363153,0.000933032,0.00007172453,0.00003201246,0.00001106988,0.00007303803,0.00233896,0.9941729,0.001193535,0.0003543107,0.000231047],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7413456,0.00001409226,0.2572204,0.00004238221,0.0003590015,0.0002454948,0.00002433298,0.0007148535,0.00003380914],"genre_scores_gemma":[0.9948727,0.0000268387,0.004739332,0.000006492779,0.0001143975,0.0001748991,0.000002798179,0.00004135264,0.00002121133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.253527,"threshold_uncertainty_score":0.9880506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0285115485019263,"score_gpt":0.2564460121458624,"score_spread":0.2279344636439361,"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."}}