{"id":"W4411393115","doi":"10.20944/preprints202506.1305.v1","title":"Large-Scale Spatio-Temporal Patterns of Burned Areas and Fire-Driven Mortality in Boreal Forests (North America)","year":2025,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Taiga; Boreal; Scale (ratio); Geography; Physical geography; Environmental science; Ecology; Forestry; Cartography; Biology; Archaeology","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":[0.0003256205,0.0001311868,0.0001334686,0.0005100829,0.000256713,0.0003780978,0.0001256272,0.0001332117,0.0004554542],"category_scores_gemma":[0.0005072503,0.00008720495,0.0001797373,0.0007073777,0.0002059654,0.0002263802,0.0001865238,0.0001256046,0.00005273735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003793858,"about_ca_system_score_gemma":0.0003084345,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09894058,"about_ca_topic_score_gemma":0.2209399,"domain_scores_codex":[0.9999013,0.00001648601,0.000009183447,0.0000372853,0.00001605379,0.00001966004],"domain_scores_gemma":[0.999607,0.00007595678,0.0001577063,0.00002579739,0.00005647687,0.00007709643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006453008,0.00003326327,0.9926433,0.00002000122,0.00004246031,0.00006343568,0.0003707201,0.0004357289,0.001274749,0.00003132654,0.00023916,0.004781308],"study_design_scores_gemma":[3.663806e-7,0.000003666226,0.9996876,0.000001321029,0.000002687505,0.00001453622,0.0000968423,0.0001170083,0.00001857334,0.000005976836,0.0000505994,9.130634e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992043,0.000147699,0.00007245596,0.00001688047,0.00000304,0.00000186314,0.0003459531,0.000004857336,0.0002028585],"genre_scores_gemma":[0.9990963,0.0001057142,0.0001658087,0.000007531485,0.000005326172,0.000003656455,0.0004917992,0.000001491515,0.0001224426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9010594,"threshold_uncertainty_score":0.1967294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03221514049983228,"score_gpt":0.2953000228170153,"score_spread":0.263084882317183,"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."}}