{"id":"W7084049393","doi":"10.6084/m9.figshare.30178371","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":"Figshare","topic":"Education and Digital Technologies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Vegetation (pathology); Probability distribution; Underpinning; Global warming; Abiotic component","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":[0.0003252228,0.0002099281,0.0001038948,0.0005075979,0.0005617646,0.000512078,0.0002989698,0.0002098793,0.001167993],"category_scores_gemma":[0.0008272964,0.000123328,0.000334365,0.0007787874,0.0002109346,0.0003027511,0.0002601983,0.0002515559,0.0001011323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008379459,"about_ca_system_score_gemma":0.004083958,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8819938,"about_ca_topic_score_gemma":0.9487076,"domain_scores_codex":[0.9998689,0.00001478535,0.000004523888,0.00002219665,0.00004379578,0.00004580518],"domain_scores_gemma":[0.9996873,0.00005604262,0.00004106136,0.00001567237,0.0001496992,0.00005023225],"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":[0.0002407823,0.00004738885,0.6895374,0.00005117457,0.0001248981,0.0001931378,0.0002615152,0.2818133,0.001690709,0.002257868,0.00274528,0.02103656],"study_design_scores_gemma":[0.0000174889,0.00005402652,0.7093937,0.00002864471,0.0000607542,0.0001271922,0.001057105,0.2835617,0.001092196,0.001269359,0.003305556,0.00003232692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920512,0.000108105,0.001378892,0.0001585695,0.000004151002,0.00001089696,0.003742628,0.00005890367,0.002486737],"genre_scores_gemma":[0.9953977,0.000132321,0.001446298,0.00001762417,0.000001361904,0.000007293475,0.002415564,0.000005202162,0.000576732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1180062,"threshold_uncertainty_score":0.2374022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09920671157557188,"score_gpt":0.3201717018622497,"score_spread":0.2209649902866779,"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."}}