{"id":"W1999412225","doi":"10.1016/j.jnucmat.2007.01.190","title":"Hydrocarbon injection for quantification of chemical erosion yields in tokamaks","year":2007,"lang":"en","type":"article","venue":"Journal of Nuclear Materials","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Divertor; Hydrocarbon; ASDEX Upgrade; Erosion; Methane; Tokamak; Flux (metallurgy); Yield (engineering); Carbon fibers; Deposition (geology); Jet (fluid); Chemistry; Materials science; Plasma; Nuclear physics; Mechanics; Geology; Metallurgy; Composite material; 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":[0.0003991263,0.0002611639,0.0002037834,0.0004295511,0.0003002171,0.0003779114,0.0002552141,0.0004190395,0.0007151994],"category_scores_gemma":[0.0003921083,0.0001914278,0.0001333237,0.0003581417,0.0003812292,0.0003776896,0.0003271932,0.0004025144,0.0001724653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004766354,"about_ca_system_score_gemma":0.0003135474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00177187,"about_ca_topic_score_gemma":0.002738469,"domain_scores_codex":[0.9997433,0.00004741939,0.000008567315,0.00005746409,0.00009874674,0.0000444674],"domain_scores_gemma":[0.9997899,0.00007269484,0.00004815304,0.00002222512,0.00004905611,0.00001791916],"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":[0.0002985674,0.00002449243,0.001613233,0.00003734935,0.000008779877,0.00003264218,0.00003887902,0.0006545133,0.9939447,0.0002946227,0.00002744291,0.003024741],"study_design_scores_gemma":[0.00001042064,0.0001038824,0.004562808,0.000004979472,0.00001062398,0.00004132691,0.00001829294,0.007400221,0.9873297,0.00006865196,0.0004404936,0.000008550457],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762734,0.001189141,0.01995841,0.00004625189,0.00001972735,0.00004847915,0.0003781435,0.0001258435,0.001960515],"genre_scores_gemma":[0.9883503,0.0008446489,0.009053865,0.00001863434,0.00001044236,0.00002475085,0.000166136,0.0000220418,0.001509149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00177187,"threshold_uncertainty_score":0.003523111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02028772709571225,"score_gpt":0.2883478955412654,"score_spread":0.2680601684455531,"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."}}