{"id":"W2792010672","doi":"10.3390/fire1010009","title":"Defining Extreme Wildfire Events: Difficulties, Challenges, and Impacts","year":2018,"lang":"en","type":"article","venue":"Fire","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":494,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"European Regional Development Fund; Fundação para a Ciência e a Tecnologia","keywords":"Damages; Terminology; Natural disaster; Natural hazard; Environmental resource management; Event (particle physics); Geography; History; Environmental science; Meteorology; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002180834,0.0001660033,0.0001567332,0.00001479248,0.0001625403,0.000019229,0.0001639914,0.00008839054,0.0003971291],"category_scores_gemma":[0.00009362336,0.0001411425,0.0000299425,0.0000842688,0.000130376,0.0002469487,0.0001809215,0.00009191018,0.001618775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001161021,"about_ca_system_score_gemma":0.000006112593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007720358,"about_ca_topic_score_gemma":0.0007560685,"domain_scores_codex":[0.9988571,0.00006203989,0.0001513141,0.0003482861,0.0002372754,0.0003440333],"domain_scores_gemma":[0.999426,0.00006033484,0.00007082794,0.0002849288,0.000003629056,0.0001542942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000060516,0.0002254744,0.1282694,0.0001081553,0.00005862584,0.00004939219,0.009041226,0.000003631189,0.004283056,0.0003613029,0.03839187,0.8191473],"study_design_scores_gemma":[0.0005253492,0.0003330592,0.9476348,0.0001802258,0.0000130239,0.00006337144,0.0001698775,0.003128619,0.000321044,0.0001324632,0.04714272,0.0003554725],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879593,0.003463492,0.00000474146,0.0004887066,0.0002611839,0.0001893961,0.000006546417,0.000103866,0.007522741],"genre_scores_gemma":[0.9986869,0.0003200255,0.0002236415,0.0001560099,0.0001250413,0.00001470847,0.000005937343,0.00002371878,0.0004440927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8193653,"threshold_uncertainty_score":0.9991586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01626572306387481,"score_gpt":0.2159246683897756,"score_spread":0.1996589453259008,"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."}}