{"id":"W4400978989","doi":"10.1109/fleps61194.2024.10604049","title":"An extrusion printed capacitively interrogated DC electric field sensor","year":2024,"lang":"en","type":"article","venue":"","topic":"Magneto-Optical Properties and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Mitacs; Manitoba Hydro","keywords":"Extrusion; Electrical engineering; Electric field; Materials science; 3d printed; Field (mathematics); Optoelectronics; Mechanical engineering; Computer science; Engineering; Physics; Composite material; Manufacturing engineering; Mathematics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00003444314,0.00008774865,0.00006793196,0.00005730645,0.00002991051,0.00005931883,0.00007878517,0.0000570369,0.001574949],"category_scores_gemma":[0.00001290536,0.00006733707,0.0000303979,0.000208302,0.000006921028,0.00007916387,0.00001291007,0.0001639436,0.0002894601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002565719,"about_ca_system_score_gemma":0.000005736763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004049298,"about_ca_topic_score_gemma":0.00001012867,"domain_scores_codex":[0.9995187,0.000007767883,0.0001202896,0.0001411818,0.000056508,0.0001555468],"domain_scores_gemma":[0.9997339,0.00003892112,0.000003080439,0.0001359155,0.00001954228,0.00006861365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007703792,0.0000284471,0.000009311602,0.00008837601,0.00002608777,0.000008918513,0.0002335081,0.000658846,0.8981652,0.01739847,0.00345303,0.07992215],"study_design_scores_gemma":[0.00004684355,0.00009784461,0.00008297996,0.0000253633,0.00000945565,0.000007592319,0.00008836992,0.802705,0.158208,0.0002392091,0.03834848,0.0001408324],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7896599,0.0003350809,0.09925009,0.0007702912,0.0001940488,0.0002463716,0.000003967594,0.002067394,0.1074729],"genre_scores_gemma":[0.9964718,0.00003698375,0.0009907392,0.0001134859,0.00006106266,0.00002341383,0.000004710686,0.00001956926,0.002278197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8020462,"threshold_uncertainty_score":0.9993377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01088638376919757,"score_gpt":0.2281146523947674,"score_spread":0.2172282686255698,"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."}}