{"id":"W3135383665","doi":"10.20944/preprints202103.0081.v1","title":"Sensing and Delineating Mixed-VOC Composition in Air Using a Single Metal-Oxide Sensor","year":2021,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Pollutant; Acetone; Oxide; Volatile organic compound; Extraction (chemistry); Environmental science; Air quality index; Sensor array; Chemistry; Biological system; Environmental chemistry; Materials science; Analytical Chemistry (journal); Computer science; Chromatography; Meteorology; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000155959,0.0005066539,0.0007081676,0.0002388576,0.00006727737,0.00002791879,0.0002246198,0.0005778837,0.00001378755],"category_scores_gemma":[0.0003648617,0.0006249062,0.000134537,0.0002679845,0.0001166543,0.0001521167,0.001370088,0.001370246,0.00001468628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005647378,"about_ca_system_score_gemma":0.00001335132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001605366,"about_ca_topic_score_gemma":0.00005075286,"domain_scores_codex":[0.9976039,0.00007316411,0.0006987104,0.0008848297,0.000233457,0.0005059313],"domain_scores_gemma":[0.9987036,0.0001468598,0.0001649797,0.0007864927,0.0001087648,0.00008931095],"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":[0.000005631657,0.00002441086,0.01135314,0.0002782114,0.00005729563,0.00007796957,0.0001466198,0.2719085,0.7150459,0.000004285945,3.240372e-7,0.001097684],"study_design_scores_gemma":[0.000215636,0.000003042333,0.005278085,0.0007746971,0.00005640094,0.00008660598,0.0004866894,0.1241581,0.8679833,0.0003849491,0.00002613268,0.0005462576],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853008,0.0005510207,0.01191091,0.00005763132,0.0002507829,0.0003409603,0.00001044108,0.001218005,0.0003593859],"genre_scores_gemma":[0.9543948,0.0001125422,0.04522986,0.00002750045,0.00006557426,0.00001135013,0.0000422784,0.0001062366,0.000009866302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1529374,"threshold_uncertainty_score":0.9996202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08753056850110734,"score_gpt":0.3041338530866838,"score_spread":0.2166032845855764,"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."}}