{"id":"W4413915441","doi":"10.1021/acs.estlett.5c00776","title":"Emissions of Ozone-Layer-Depleting Methyl Chloroform (CH<sub>3</sub>CCl<sub>3</sub>) in China Inferred from High-Frequency In-Situ Observations","year":2025,"lang":"en","type":"article","venue":"Environmental Science & Technology Letters","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"In situ; Ozone; Chloroform; China; Ozone layer; Environmental chemistry; Environmental science; Atmospheric sciences; Chemistry; Geology; Geography; Organic chemistry","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":[0.0002133033,0.0003255792,0.0001451916,0.0003672169,0.000287794,0.0002515705,0.0002276503,0.0002267494,0.0002082656],"category_scores_gemma":[0.0001489332,0.0002034966,0.0002499014,0.0004495511,0.0002340452,0.0002223515,0.0002081086,0.0001636888,0.00004534046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008113419,"about_ca_system_score_gemma":0.0005944669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06485884,"about_ca_topic_score_gemma":0.1038868,"domain_scores_codex":[0.9999267,0.000009410758,0.000004565965,0.00002472352,0.00001837086,0.00001628443],"domain_scores_gemma":[0.9998806,0.00001749348,0.00003513172,0.00001178533,0.00003826401,0.00001676619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001346722,0.00006754798,0.8268028,0.00007619042,0.0001359658,0.0003021093,0.0003595353,0.01204434,0.1483973,0.0002412082,0.0004952154,0.01094299],"study_design_scores_gemma":[0.000008170577,0.00002587845,0.9784289,0.000002865061,0.00003824634,0.00002718128,0.0001019733,0.01189411,0.008863475,0.00005559432,0.0005419579,0.00001169748],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992156,0.0000254808,0.0003499854,0.00001506209,0.000001153089,0.000002899916,0.0001709626,0.000009048987,0.0002097423],"genre_scores_gemma":[0.9989967,0.00004797829,0.000473233,0.00001152723,0.000001909498,0.000004910236,0.0003033458,0.000003012499,0.000157448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06485884,"threshold_uncertainty_score":0.1289627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008144509846541918,"score_gpt":0.2031880630243342,"score_spread":0.1950435531777923,"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."}}