{"id":"W4313511855","doi":"10.5194/acp-2022-829","title":"Spatio-temporal variation characteristics of global wildfires and their emissions","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Environmental science; Context (archaeology); Climate change; Latitude; Climatology; Physical geography; Spatial distribution; Atmospheric sciences; Terrestrial ecosystem; Geography; Ecosystem; Remote sensing; Ecology; Geology","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":[0.0003505935,0.0001878485,0.0001612265,0.0008115638,0.0001294757,0.0003434819,0.0001357012,0.0001638516,0.0006016165],"category_scores_gemma":[0.000472758,0.00007286948,0.0002917603,0.00126336,0.0001217996,0.0002765763,0.0002062348,0.0001569985,0.0001168934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002531648,"about_ca_system_score_gemma":0.0001477181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01301742,"about_ca_topic_score_gemma":0.02196165,"domain_scores_codex":[0.9998578,0.00001789216,0.00001590269,0.00005285916,0.00003136096,0.00002418931],"domain_scores_gemma":[0.9995551,0.00008221879,0.0001601079,0.00004430944,0.0001156948,0.00004253325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004271356,0.00001498038,0.9906117,0.00002812448,0.0001111402,0.00009710614,0.0001226894,0.00171996,0.001438343,0.00009635661,0.0002787341,0.005438179],"study_design_scores_gemma":[8.739752e-7,0.000005182482,0.998059,0.000004650866,0.00001317698,0.00003971616,0.0001123092,0.001292761,0.0001453755,0.00002997625,0.0002941167,0.000002895135],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974489,0.0001837122,0.0002916027,0.00001854426,0.000005918353,0.000003046019,0.001514334,0.00001380346,0.0005201163],"genre_scores_gemma":[0.9980921,0.00008074343,0.0001829524,0.000006925891,0.000005871507,0.00000446478,0.001459434,0.000003021309,0.000164472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01301742,"threshold_uncertainty_score":0.02588332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01285901616667634,"score_gpt":0.2324134070872191,"score_spread":0.2195543909205428,"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."}}