{"id":"W4322501658","doi":"10.3390/atmos14030461","title":"Is There a Formaldehyde Deficit in Emissions Inventories for Southeast Michigan?","year":2023,"lang":"en","type":"article","venue":"Atmosphere","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Formaldehyde; Ozone; Environmental science; Air quality index; Environmental chemistry; Volatile organic compound; Air pollution; Pollutant; Emission inventory; National Ambient Air Quality Standards; Meteorology; Atmospheric sciences; Chemistry; Organic chemistry; Geography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002331318,0.000171436,0.0001863496,0.000001341623,0.0002061457,0.00005031036,0.0002404758,0.0001185629,0.002817202],"category_scores_gemma":[0.00009088797,0.0001422706,0.0001049886,0.0004766746,0.00005330295,0.0001465124,0.00001830085,0.0001301429,0.0003422433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003647869,"about_ca_system_score_gemma":0.00006892123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005397094,"about_ca_topic_score_gemma":0.00208203,"domain_scores_codex":[0.9988298,0.00002668914,0.0002373043,0.0002825718,0.0001555183,0.0004680689],"domain_scores_gemma":[0.9993608,0.0002024002,0.00006331867,0.0002124353,0.00002476182,0.0001362892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006808855,0.00002192233,0.9769292,0.0001177598,0.00002301356,0.0000187924,0.001520348,0.002497748,0.000162072,0.00008849885,0.009015037,0.00953756],"study_design_scores_gemma":[0.002901179,0.0004173894,0.5937677,0.0004077084,0.00006247218,0.00002619585,0.04215718,0.09874377,0.002757486,0.01259896,0.2446349,0.001525037],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891145,0.0005604595,0.0001458187,0.0006578525,0.000150456,0.0002469204,0.0001428777,0.0001369253,0.008844173],"genre_scores_gemma":[0.9915795,0.00005107434,0.00149078,0.0002700136,0.0001299685,0.00001373582,0.0001483021,0.000009853445,0.006306744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3831615,"threshold_uncertainty_score":0.9980944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0219844446534088,"score_gpt":0.2379492263534249,"score_spread":0.2159647817000161,"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."}}