{"id":"W4414391137","doi":"10.1080/07038992.2025.2560347","title":"Projected Future Changes in Burn Probability in Canada’s Forests and Communities Under Different Climate Change Scenarios","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service; University of British Columbia","funders":"","keywords":"Climate change; Vegetation (pathology); Probability distribution; Underpinning; Abiotic component; Distribution (mathematics); Global warming","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.0004091458,0.0002437138,0.0001187554,0.0005646486,0.0006195454,0.0005206991,0.0003157838,0.0002151198,0.001028705],"category_scores_gemma":[0.0008303659,0.0001280966,0.0004074764,0.0007162347,0.0002066913,0.0003246391,0.0002774452,0.0002556206,0.00008515977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009145769,"about_ca_system_score_gemma":0.004804825,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8987477,"about_ca_topic_score_gemma":0.9494213,"domain_scores_codex":[0.9998446,0.00001946431,0.000005748353,0.00002667412,0.00004782998,0.00005580554],"domain_scores_gemma":[0.999684,0.00005222354,0.00004341147,0.00001545346,0.0001499075,0.00005503935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002905576,0.00006317651,0.7157937,0.00005890029,0.0001827526,0.0002184898,0.0002865812,0.2580858,0.002044749,0.002227245,0.002406271,0.01834167],"study_design_scores_gemma":[0.00002295434,0.00006332398,0.7711739,0.00003090261,0.00008110198,0.000133358,0.001014467,0.2228832,0.0008849375,0.000986963,0.002689602,0.00003530004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938736,0.0001097659,0.0009049916,0.0001344553,0.000003877687,0.00001081389,0.00288776,0.00004111427,0.002033591],"genre_scores_gemma":[0.9964097,0.0001296718,0.001051417,0.00001718642,0.000001278274,0.000007278158,0.001926354,0.000003777256,0.0004533646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1012523,"threshold_uncertainty_score":0.2036972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01592374976178509,"score_gpt":0.2091228203231382,"score_spread":0.1931990705613531,"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."}}