{"id":"W4366777714","doi":"10.54097/hset.v45i.7334","title":"The Impacts Of COVID-19 Pandemic on Greenhouse Gas Emissions and Climate Change","year":2023,"lang":"en","type":"article","venue":"Highlights in Science Engineering and Technology","topic":"COVID-19 impact on air quality","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Pandemic; Climate change; Context (archaeology); Global warming; Coronavirus disease 2019 (COVID-19); Outbreak; Population; Environmental science; Natural resource economics; Socioeconomic status; Environmental health; Geography; Medicine; Economics; Ecology","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":[0.001245477,0.0001210882,0.0001410231,0.0004010417,0.0002882178,0.00002371592,0.0003596481,0.00009499354,0.000006668337],"category_scores_gemma":[0.001153855,0.00008091623,0.0000125712,0.002203064,0.001099792,0.0001378689,0.0004411159,0.0001642751,0.00003922854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001791917,"about_ca_system_score_gemma":0.00003068299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002323277,"about_ca_topic_score_gemma":0.0002511379,"domain_scores_codex":[0.9987128,0.00001807762,0.0001877658,0.0003330115,0.0002522069,0.0004960862],"domain_scores_gemma":[0.9990395,0.0003526933,0.0000568507,0.0003466046,0.000005009801,0.0001992959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000502782,0.0001118133,0.6742571,0.0001341563,0.000008902225,0.00007953819,0.004111339,0.002824368,0.1910766,0.09548821,0.0005383546,0.03131937],"study_design_scores_gemma":[0.001567771,0.0007639912,0.8434209,0.0002381677,0.00001624951,0.0001362314,0.0008742615,0.04643298,0.01435766,0.009454434,0.08184292,0.0008944035],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902933,0.00006572081,0.00002225623,0.009006438,0.00008901332,0.0001610374,0.000007172565,0.000303029,0.00005203381],"genre_scores_gemma":[0.9977211,0.00202447,0.0001001696,0.000104008,0.000008790755,0.00002361739,2.92211e-7,0.00000779022,0.000009786621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1767189,"threshold_uncertainty_score":0.405223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03577196978442496,"score_gpt":0.3107668078586839,"score_spread":0.274994838074259,"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."}}