{"id":"W37340209","doi":"10.1007/s11764-023-01384-3","title":"高温アルミナイジング処理したステンレス鋼における合成層の形成とアブレシブ摩耗特性(表面処理・腐食)","year":2008,"lang":"en","type":"article","venue":"鐵と鋼 : 日本鐡鋼協會々誌","topic":"Childhood Cancer Survivors' Quality of Life","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alberta Children's Hospital Research Institute","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003022282,0.0001699745,0.0002513133,0.0006622782,0.001300879,0.00183168,0.0003406092,0.0006915036,0.00745759],"category_scores_gemma":[0.005095765,0.0002343319,0.0003635667,0.0004212826,0.002555348,0.001578899,0.0006487466,0.001406762,0.00196233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001209117,"about_ca_system_score_gemma":0.001263789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002734538,"about_ca_topic_score_gemma":0.005525891,"domain_scores_codex":[0.9989341,0.0003453449,0.0001273524,0.0001247459,0.0003543393,0.0001141748],"domain_scores_gemma":[0.9964116,0.0009676755,0.0008898426,0.000267444,0.001072825,0.0003907006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005353248,0.0005339654,0.1071828,0.001232543,0.0001986161,0.005185558,0.01282027,0.0006824958,0.03948054,0.07171517,0.02985467,0.730578],"study_design_scores_gemma":[0.0001617594,0.0017119,0.258038,0.001659286,0.0004212915,0.03746522,0.02007637,0.001744173,0.08146088,0.07650407,0.5204319,0.0003252606],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6605171,0.03674766,0.03161331,0.0279825,0.002265987,0.0004529845,0.0005380923,0.0002491179,0.2396332],"genre_scores_gemma":[0.9446016,0.01152513,0.01412058,0.001997632,0.000723471,0.0001392346,0.0002236576,0.00003651667,0.02663219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00745759,"threshold_uncertainty_score":0.02494812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05245255692464051,"score_gpt":0.3222279094455803,"score_spread":0.2697753525209398,"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."}}