{"id":"W4309121642","doi":"10.1002/essoar.10512804.1","title":"Electron Temperature Inference from Multiple Fixed Bias Langmuir Probes","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Semiconductor materials and devices","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Norges Forskningsråd; Universitetet i Oslo; European Commission","keywords":"Langmuir probe; Electron temperature; Electron; Computational physics; Plasma; Electron density; Ranging; Plasma diagnostics; Ground truth; Temperature measurement; Physics; Computer science; Geodesy; Geology; Artificial intelligence; Thermodynamics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007739517,0.0003188078,0.0003622676,0.00007182362,0.00004709209,0.0001996567,0.0003699282,0.0002784574,0.004492069],"category_scores_gemma":[0.00004887267,0.0002801808,0.00008097527,0.0000699259,0.00001106137,0.00007104847,0.0003685205,0.0006254063,0.00006024225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008410471,"about_ca_system_score_gemma":0.00005031523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001264528,"about_ca_topic_score_gemma":0.0003496905,"domain_scores_codex":[0.9989042,0.00004359873,0.0002558496,0.0003606866,0.0001785337,0.000257079],"domain_scores_gemma":[0.9992992,0.0001158505,0.00005031655,0.000450742,0.00002772943,0.00005615841],"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":[0.00001400108,0.00003080221,0.007409827,0.0004512872,0.0001756894,0.00001041372,0.0005344786,0.01643817,0.965624,0.0001160943,0.009083286,0.0001119169],"study_design_scores_gemma":[0.0004627666,0.00004576421,0.01183366,0.0001870036,0.00005786431,0.000001996624,0.0002827062,0.006270162,0.9216746,0.001482005,0.05639291,0.001308532],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918169,0.002268379,0.00001470001,0.00002926033,0.001913509,0.000300425,0.0004212156,0.0009871743,0.002248486],"genre_scores_gemma":[0.9963645,0.0003057552,0.0008519174,0.00007651447,0.0003653642,0.0001679621,0.001091287,0.00006433668,0.0007123636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04730963,"threshold_uncertainty_score":0.999965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03069138416641573,"score_gpt":0.2488457594703608,"score_spread":0.2181543753039451,"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."}}