{"id":"W3214436320","doi":"10.32920/ryerson.14647959.v1","title":"Development of a Device Characterization Curve Tracer for High Power Application","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Silicon Carbide Semiconductor Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Device under test; Calibration; Voltage; Power (physics); Observational error; Characterization (materials science); Accuracy and precision; Transient (computer programming); Measurement uncertainty; Temperature measurement; Range (aeronautics); Electronic engineering; Materials science; Electrical engineering; Computer science; Engineering; Scattering parameters; Physics","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":[0.001065489,0.0005607554,0.000597047,0.0008962508,0.0002677168,0.0009563476,0.001836266,0.0008129896,0.004196348],"category_scores_gemma":[0.002639116,0.0003388917,0.0003711258,0.0007764972,0.0002883595,0.001343049,0.000567057,0.0009339801,0.001366232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009663312,"about_ca_system_score_gemma":0.001005608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008150701,"about_ca_topic_score_gemma":0.000993904,"domain_scores_codex":[0.9989492,0.0001242365,0.00004850683,0.0001637384,0.0006617303,0.00005259725],"domain_scores_gemma":[0.9982935,0.0004238482,0.0002168886,0.0002721812,0.0007254151,0.00006811925],"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":[0.000390028,0.0002905311,0.005067261,0.0007468036,0.00008908195,0.0004390793,0.0006167685,0.01801808,0.6908166,0.01032756,0.007222675,0.2659755],"study_design_scores_gemma":[0.00004517137,0.0006945254,0.004011289,0.00009490724,0.00004536578,0.000980061,0.000098378,0.1723072,0.7716392,0.001543436,0.04844339,0.00009723716],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0333117,0.0004771909,0.9492607,0.0001433219,0.0001373568,0.0004000177,0.0004629263,0.01147611,0.004330667],"genre_scores_gemma":[0.4433222,0.000672539,0.5391832,0.0002405502,0.00004790031,0.000802558,0.001225071,0.001264783,0.01324118],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004196348,"threshold_uncertainty_score":0.01403815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02101189584654933,"score_gpt":0.2443445663089847,"score_spread":0.2233326704624354,"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."}}