{"id":"W6963967453","doi":"10.25316/ir-17528","title":"Mapping the geospatial distribution of atmospheric BTEX compounds using portable mass spectrometry and adaptive whole air sampling","year":2020,"lang":"en","type":"article","venue":"VIUspace","topic":"Indoor Air Quality and Microbial Exposure","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sampling (signal processing); Instrumentation (computer programming); BTEX; Adaptive sampling; Geospatial analysis; Sample (material); Mass spectrometry; Air monitoring","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001966517,0.0001117993,0.0001593215,0.000003033696,0.0002163162,0.00002114744,0.0001296476,0.00005572873,0.0001044627],"category_scores_gemma":[0.00003241068,0.00009207613,0.00004522961,0.0003881762,0.0001760809,0.0001359697,0.0001407235,0.0001529615,0.00002018516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001013088,"about_ca_system_score_gemma":0.00001473169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009825615,"about_ca_topic_score_gemma":0.0001532618,"domain_scores_codex":[0.9991599,0.00006132359,0.0001721638,0.0002177669,0.000169442,0.0002193547],"domain_scores_gemma":[0.99963,0.00004504629,0.0001289963,0.0001208152,0.000009901707,0.00006521195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00007146915,0.00004537936,0.0178639,0.00003776069,0.00004045123,0.000004892067,0.004272837,0.01985783,0.9538109,0.0004097514,0.002414743,0.001170121],"study_design_scores_gemma":[0.003534983,0.001184725,0.4831326,0.0003089385,0.0002304515,0.00009335009,0.03321226,0.2424648,0.09545156,0.001948454,0.136419,0.002018899],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8273848,0.00009838912,0.1703566,0.001245674,0.0000567379,0.0001607756,0.00003814153,0.00002285213,0.0006359899],"genre_scores_gemma":[0.9882445,0.000007880104,0.01131842,0.0002691367,0.00006081522,0.000001317016,0.00001646979,0.000008794457,0.00007272253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8583593,"threshold_uncertainty_score":0.3754756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0299307678340191,"score_gpt":0.2301481708122259,"score_spread":0.2002174029782068,"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."}}