{"id":"W4221001227","doi":"10.5194/egusphere-egu22-7970","title":"Dynamics of fires, harvest and carbon stocks in U.S. forests 1926-2017","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Biomass (ecology); Clearing; Environmental science; Biomass burning; Agriculture; Ecology; Geography; Biology; Meteorology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002604237,0.0001635592,0.0001401296,0.0008273756,0.0003292886,0.000672748,0.0002208092,0.0002242149,0.001993572],"category_scores_gemma":[0.0006753735,0.000104136,0.0002357723,0.001635966,0.0002569535,0.000457372,0.0004666014,0.0004451363,0.0004426107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007057422,"about_ca_system_score_gemma":0.0005102385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07815219,"about_ca_topic_score_gemma":0.162772,"domain_scores_codex":[0.9999213,0.0000116533,0.000008707418,0.00001788027,0.00001781092,0.00002262801],"domain_scores_gemma":[0.9995467,0.00005988829,0.0001961999,0.00002191986,0.0000979607,0.00007732019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007050389,0.00003999217,0.9892969,0.0000204871,0.00005324776,0.00009461601,0.0003419546,0.0005921109,0.0001692966,0.0002625537,0.00224451,0.006813825],"study_design_scores_gemma":[0.000002336958,0.00001167417,0.996988,0.00001391462,0.000009981755,0.00005354864,0.0006933603,0.0005992593,0.00007300187,0.00007563108,0.00147501,0.00000421189],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938591,0.0004387042,0.00006567603,0.0001982104,0.00002370444,0.000003361043,0.004194164,0.00001021777,0.001206938],"genre_scores_gemma":[0.9943346,0.0004384139,0.00008037336,0.00003728512,0.00004053589,0.000008084802,0.004229642,0.000005307738,0.0008258607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07815219,"threshold_uncertainty_score":0.1553946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007757690943493677,"score_gpt":0.2228779130623056,"score_spread":0.215120222118812,"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."}}