{"id":"W2981701263","doi":"10.5897/jmer2014.0327","title":"Establishment of an air quality monitoring model for dust-free rooms using neural network and control chart techniques","year":2014,"lang":"en","type":"article","venue":"Mechanical Engineering Research","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ventilation (architecture); Environmental science; Pollution; Indoor air quality; Pollutant; Air pollution; Environmental engineering; Waste management; Automotive engineering; Process engineering; Engineering; Mechanical engineering; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005364926,0.0001533871,0.0002811113,0.00005500603,0.0002011852,0.00003986866,0.0003883989,0.000130282,0.000004949673],"category_scores_gemma":[0.001089331,0.0001496328,0.00005606289,0.0002085907,0.00007937058,0.0002207583,0.0003877838,0.0003716744,6.646433e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001478558,"about_ca_system_score_gemma":0.000009052724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002359116,"about_ca_topic_score_gemma":0.00000392849,"domain_scores_codex":[0.9978444,0.000156875,0.000365444,0.0003844238,0.0006071463,0.0006416954],"domain_scores_gemma":[0.9986551,0.0005542305,0.00006118745,0.0004563264,0.00004732867,0.0002257745],"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":[0.00008025306,0.00006470021,0.001738032,0.000120592,0.00001183732,7.596673e-7,0.0001663988,0.880551,0.09949751,0.0009148038,0.00002331496,0.01683074],"study_design_scores_gemma":[0.00033994,0.0002207558,0.001500409,0.00006826335,0.0000070429,0.000001784691,0.00003290723,0.977009,0.01919183,0.001410935,0.00006215522,0.0001549688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.70129,0.00001824706,0.2980605,0.00008643462,0.0001071528,0.0003177615,0.000006292755,0.00009456218,0.00001911708],"genre_scores_gemma":[0.932197,0.000002902683,0.06728847,0.000006974709,0.0003832473,0.00006268748,0.000001430033,0.00003119744,0.00002604593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2309071,"threshold_uncertainty_score":0.610185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08952278254458702,"score_gpt":0.3568332598811408,"score_spread":0.2673104773365538,"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."}}