{"id":"W4287846867","doi":"10.1109/eic51169.2022.9833208","title":"Additive Manufactured Dielectrics for Aerospace Electrical Insulation Applications","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Dielectric; Materials science; Stereolithography; Composite material; Context (archaeology); Dielectric strength; Dielectric spectroscopy; Aerospace; Anisotropy; Dielectric loss; Optoelectronics; Optics","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":[0.0004013896,0.0003667866,0.0001906795,0.0005815884,0.0002397753,0.0009949935,0.0003532511,0.0005369958,0.002465935],"category_scores_gemma":[0.0008944324,0.0001951716,0.0002972483,0.0004856676,0.0002431032,0.0005536302,0.000348427,0.0005767645,0.001448965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002127546,"about_ca_system_score_gemma":0.0002038683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001004625,"about_ca_topic_score_gemma":0.0003642734,"domain_scores_codex":[0.9994191,0.00008614888,0.00003184164,0.00006460294,0.0003639109,0.00003445352],"domain_scores_gemma":[0.9993393,0.0001936154,0.0001350694,0.0001422866,0.0001668491,0.00002279838],"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":[0.00007325209,0.00003969542,0.001219723,0.0006618694,0.00002148494,0.0004468961,0.0001466309,0.00171967,0.8986976,0.005130391,0.0007401891,0.09110251],"study_design_scores_gemma":[0.000007357937,0.0004576968,0.003251412,0.00008995101,0.00004915962,0.002062435,0.0001371751,0.003243276,0.9094645,0.001198688,0.0800227,0.00001565781],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6340479,0.02830686,0.2774709,0.0007189311,0.001067081,0.000129696,0.0005023042,0.001160218,0.05659608],"genre_scores_gemma":[0.8757015,0.007509361,0.1014613,0.0002163167,0.0001661937,0.00004656811,0.0003493185,0.0002013294,0.01434804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002465935,"threshold_uncertainty_score":0.008249342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01547744106838907,"score_gpt":0.2477042584165904,"score_spread":0.2322268173482013,"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."}}