{"id":"W2027059031","doi":"10.1111/j.1939-7445.2001.tb00071.x","title":"FIRE DISTURBANCE PATTERNS AND FOREST AGE STRUCTURE","year":2001,"lang":"en","type":"article","venue":"Natural Resource Modeling","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Forest Service","funders":"","keywords":"Disturbance (geology); Distribution (mathematics); Age structure; Exponential distribution; Stability (learning theory); Ecology; Stable distribution; Geography; Physical geography; Environmental science; Demography; Biology; Mathematics; Statistics; Population; Computer science; Paleontology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004565302,0.0001228063,0.0001039471,0.0004982399,0.0001238906,0.0005599551,0.0001314302,0.0001860653,0.001224096],"category_scores_gemma":[0.002722053,0.00007632247,0.0001100923,0.0003967993,0.0001841013,0.0003914146,0.0001506439,0.0001380005,0.0001850344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003440431,"about_ca_system_score_gemma":0.00009901365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001890758,"about_ca_topic_score_gemma":0.002891006,"domain_scores_codex":[0.9999191,0.00001954447,0.000007186964,0.00002085926,0.00001482693,0.00001860463],"domain_scores_gemma":[0.9988943,0.0004132569,0.0003916685,0.00009184463,0.0001247885,0.00008426111],"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":[0.0002370893,0.00005381446,0.9182759,0.00002822715,0.00009060242,0.0002022544,0.0001653677,0.04925269,0.004661851,0.004483775,0.0002702847,0.02227815],"study_design_scores_gemma":[0.0000133827,0.00007117444,0.8748181,0.00001454175,0.00003531747,0.0004333259,0.000147787,0.1153655,0.00195514,0.006010744,0.001121973,0.00001292948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996407,0.0001172481,0.001990328,0.00002471158,0.00000247604,0.000003345095,0.0001119507,0.00001307896,0.001329895],"genre_scores_gemma":[0.9996344,0.00002590848,0.0001190315,0.00000168717,8.236398e-7,7.60845e-7,0.00005094474,0.000001464432,0.0001650432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001890758,"threshold_uncertainty_score":0.004095018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006675862382978163,"score_gpt":0.2045392965169759,"score_spread":0.1978634341339978,"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."}}