{"id":"W604433959","doi":"","title":"41442 室内環境中の微生物発育速度・MVOC放散のモデリングと数値予測手法の開発(第11報) : 真菌増殖に関する実験結果と増殖挙動モデル定数の推定(生物汚染(1),環境工学II)","year":2008,"lang":"ja","type":"article","venue":"学術講演梗概集. D-2, 環境工学II, 熱, 湿気, 温熱感, 自然エネルギー, 気流・換気・排煙, 数値流体, 空気清浄, 暖冷房・空調, 熱源設備, 設備応用","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Metis; Computer science; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006523395,0.0003541346,0.0001309364,0.0007107259,0.001779462,0.004006838,0.0003060446,0.001390146,0.03050978],"category_scores_gemma":[0.001188732,0.0001614485,0.0002013279,0.0006716528,0.003517328,0.001964476,0.001048091,0.001121536,0.003371537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003278855,"about_ca_system_score_gemma":0.002659562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007719531,"about_ca_topic_score_gemma":0.01022973,"domain_scores_codex":[0.9996642,0.00009513441,0.00002217863,0.00006630547,0.00008887728,0.0000633484],"domain_scores_gemma":[0.9995715,0.0001205835,0.00005813824,0.00002624775,0.0001373228,0.0000861833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000851597,0.00008245535,0.005231748,0.0001411018,0.00001321474,0.0003043787,0.002991547,0.0007046665,0.001186708,0.8932342,0.01806205,0.07796285],"study_design_scores_gemma":[0.00004481795,0.0002349258,0.01556891,0.0004283165,0.00003716198,0.0008954974,0.013587,0.002298792,0.004441006,0.3972632,0.5651555,0.00004492964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05892589,0.005456345,0.007814314,0.01186483,0.0005740726,0.00006199747,0.0001285111,0.00003885468,0.9151352],"genre_scores_gemma":[0.7860278,0.004944411,0.006536521,0.001550981,0.0002574559,0.00007488763,0.0001356727,0.00002608338,0.2004461],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03050978,"threshold_uncertainty_score":0.1020653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415348800557583,"score_gpt":0.2101094138121194,"score_spread":0.1959559258065436,"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."}}