{"id":"W3162207768","doi":"10.1109/tps.2021.3076806","title":"Density–Temperature Constraint From Fixed-Bias Spherical Langmuir Probes","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Plasma Science","topic":"Laser-induced spectroscopy and plasma","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Langmuir probe; Constraint (computer-aided design); Electron temperature; Plasma; Multivariate statistics; Computational physics; Plasma diagnostics; Function (biology); Root mean square; Electron density; Square root; Materials science; Probability density function; Mean squared error; Langmuir; Simple (philosophy); Temperature measurement; Statistical physics; Physics; Statistics; Mathematics; Thermodynamics; Quantum mechanics; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002732163,0.0009583936,0.001132517,0.0005694542,0.0006379478,0.001088761,0.002556186,0.00124453,0.001567569],"category_scores_gemma":[0.0143968,0.000706272,0.0008825786,0.0006841635,0.001384186,0.002998681,0.001460408,0.002109887,0.0006668062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009408748,"about_ca_system_score_gemma":0.0009421387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005513563,"about_ca_topic_score_gemma":0.003895099,"domain_scores_codex":[0.9978266,0.0005077269,0.00008286073,0.000622544,0.0007726136,0.0001875346],"domain_scores_gemma":[0.9959623,0.002217726,0.0004810363,0.0005932742,0.000661208,0.00008442228],"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":[0.0006173894,0.0001964699,0.01102152,0.0006390678,0.0002821546,0.0009449945,0.000438815,0.2752241,0.3132795,0.3117535,0.003478316,0.08212427],"study_design_scores_gemma":[0.00001632246,0.0000654175,0.001690872,0.00001495678,0.00002347599,0.0002254825,0.00003090165,0.9134955,0.04850892,0.03416459,0.001713253,0.00005031155],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04821546,0.0005229205,0.9462526,0.0005898929,0.00005995281,0.00003146074,0.0003132675,0.0004158186,0.00359863],"genre_scores_gemma":[0.8927805,0.0005943483,0.10268,0.0004093233,0.0000883125,0.0001120135,0.000518039,0.000184162,0.002633185],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005513563,"threshold_uncertainty_score":0.01444918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01488593825308763,"score_gpt":0.2214210409061526,"score_spread":0.206535102653065,"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."}}