{"id":"W26028511","doi":"10.1016/j.chroma.2015.05.014","title":"OS-10 トラブル・リスク回避のためのリスクマップへの適用","year":2010,"lang":"en","type":"article","venue":"空気調和・衛生工学会大会　学術講演論文集","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","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":[0.001455803,0.002543061,0.00113177,0.001890337,0.0007655899,0.001369387,0.001264417,0.001024985,0.02048229],"category_scores_gemma":[0.00130638,0.0007678194,0.0007982376,0.00142153,0.001026366,0.001609631,0.001071365,0.002117765,0.01490438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005891552,"about_ca_system_score_gemma":0.001581983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006680364,"about_ca_topic_score_gemma":0.001071138,"domain_scores_codex":[0.9985161,0.0001778793,0.0001199628,0.0004953207,0.0005089793,0.0001816406],"domain_scores_gemma":[0.9989204,0.0003238153,0.0001830902,0.00014827,0.0002880911,0.0001362383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001903636,0.0004052267,0.002305663,0.001797967,0.0001560104,0.0005393817,0.000323241,0.0008905996,0.8499922,0.005571796,0.01355612,0.1225582],"study_design_scores_gemma":[0.000102077,0.001000664,0.002751818,0.0001578334,0.0001582731,0.001247127,0.0001282651,0.005141382,0.819127,0.0009965607,0.1690779,0.0001112301],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.304557,0.0208184,0.5640731,0.001074592,0.00296864,0.001697182,0.01458321,0.03946648,0.05076146],"genre_scores_gemma":[0.3302489,0.02933082,0.4704,0.002625183,0.0007535819,0.003959439,0.03782209,0.008359353,0.1165006],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02048229,"threshold_uncertainty_score":0.06852001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004169842305977752,"score_gpt":0.2122965708313563,"score_spread":0.2081267285253786,"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."}}