{"id":"W4396919201","doi":"10.1088/1742-6596/2743/1/012070","title":"Numerical simulation and experimental characterization of the TRIUMF-FEBIAD cathode temperature for optimizing the ion source performance","year":2024,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Plasma Diagnostics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; TRIUMF","funders":"","keywords":"Characterization (materials science); Cathode; Ion; Nuclear engineering; Materials science; Physics; Nanotechnology; Engineering; Electrical engineering","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":[0.0005219636,0.0002659817,0.0003916934,0.0002988395,0.0003457852,0.0005905967,0.0005751402,0.0006740083,0.001653277],"category_scores_gemma":[0.001380886,0.0001480354,0.0002688884,0.0003876215,0.000420094,0.0003175796,0.0003114975,0.0003275712,0.0002397568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007005005,"about_ca_system_score_gemma":0.000469869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002007073,"about_ca_topic_score_gemma":0.001270042,"domain_scores_codex":[0.9998494,0.00001813945,0.000005955555,0.00002462065,0.00006957151,0.00003222169],"domain_scores_gemma":[0.99954,0.0001887388,0.00005313216,0.00005536612,0.0001396395,0.00002320384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004777321,0.0001473756,0.005761304,0.0003327613,0.00002704016,0.0003671215,0.000257649,0.8175325,0.1585192,0.004775863,0.001180721,0.01062065],"study_design_scores_gemma":[0.00003554678,0.0002137246,0.002071391,0.00002074222,0.00000980703,0.00005265502,0.00007775854,0.9380349,0.05778738,0.0004665837,0.001208275,0.00002122537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9548435,0.0004356361,0.03129911,0.0003567759,0.00007801665,0.00005345698,0.000652097,0.0003146207,0.01196694],"genre_scores_gemma":[0.9923019,0.00008404466,0.006785318,0.00001404171,0.000002880046,0.0000314617,0.0001263049,0.00001738148,0.0006366163],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002007073,"threshold_uncertainty_score":0.005530775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01529684917685907,"score_gpt":0.2417001052779401,"score_spread":0.226403256101081,"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."}}