{"id":"W6902235067","doi":"10.6084/m9.figshare.29481734.v1","title":"Extremely large fires shape fire severity patterns across the diverse forests of British Columbia, Canada","year":2025,"lang":"en","type":"dataset","venue":"Figshare","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Raw data; Fire regime; Fire ecology; Scaling; Vegetation types","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001565339,0.0004925734,0.0008296621,0.00002933729,0.0006058513,0.0005589477,0.002792608,0.000549107,0.3113017],"category_scores_gemma":[0.002247616,0.000697599,0.0003131057,0.0004989522,0.00003865676,0.0002079269,0.002756859,0.001018216,0.0005930597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005645159,"about_ca_system_score_gemma":0.002313377,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9909031,"about_ca_topic_score_gemma":0.9999651,"domain_scores_codex":[0.9957779,0.0002149645,0.0006566207,0.0009168626,0.001289653,0.001143973],"domain_scores_gemma":[0.9962879,0.000338343,0.0007809152,0.001836524,0.0005359872,0.0002203046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001135372,0.0001048576,0.003456541,0.002761437,0.0001749016,0.0008478613,0.00002476586,0.000001531435,6.271754e-8,4.484597e-9,0.9914586,0.001158093],"study_design_scores_gemma":[0.0004304695,0.0000159881,0.2157628,0.008818199,0.00007162181,0.00002305425,0.0001046934,0.00006112897,5.752231e-7,0.000001073942,0.7741938,0.0005165539],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007072439,0.0009550175,2.888932e-9,0.00001614023,0.0002569459,0.001017619,0.9905881,0.00007582209,0.00001795928],"genre_scores_gemma":[0.0085412,0.00002349595,6.756345e-7,0.0004631325,0.0001704477,0.0004292999,0.9886472,0.00007355244,0.001650991],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3107086,"threshold_uncertainty_score":0.9995475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02808745421599057,"score_gpt":0.2677428191329099,"score_spread":0.2396553649169193,"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."}}