{"id":"W2144035407","doi":"10.1080/17513758.2014.950184","title":"Birth-jump processes and application to forest fire spotting","year":2014,"lang":"en","type":"article","venue":"Journal of Biological Dynamics","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Spotting; Jump; Environmental science; Mathematics; Biology; Statistics; Ecology; Geography; Computer science; Artificial intelligence; Astronomy; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0005625476,0.00008560414,0.0001666438,0.00002042454,0.00006149354,0.0000244178,0.0001762948,0.00007504079,0.00001926287],"category_scores_gemma":[0.0005877863,0.00005510004,0.0000285708,0.0001632513,0.00006009411,0.00009165367,0.00009091545,0.0001095617,0.00004614527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009006125,"about_ca_system_score_gemma":0.000004589162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003758034,"about_ca_topic_score_gemma":0.0001789579,"domain_scores_codex":[0.9992713,0.00005303028,0.0002564417,0.0001384254,0.0001361696,0.0001446257],"domain_scores_gemma":[0.999365,0.0001957621,0.0002133533,0.0000828324,0.00002139555,0.0001216689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004156652,0.00006290982,0.8086805,0.00004643932,0.000006290065,0.000003975436,0.000062264,0.00142369,0.003844918,0.0001962493,0.0001151417,0.1855161],"study_design_scores_gemma":[0.000255449,0.001042269,0.7117134,0.00005931071,0.000008034621,0.0001403812,0.00005014666,0.2781553,0.0001084055,0.001552899,0.006724896,0.0001895124],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9673145,0.00002881435,0.03167347,0.0003621757,0.00006343655,0.0001272319,0.000002563993,0.00001316441,0.000414615],"genre_scores_gemma":[0.9972544,0.00002167243,0.002422192,0.0001802352,0.00008385541,0.000004145985,0.000001524741,0.000005637381,0.00002635778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2767316,"threshold_uncertainty_score":0.2246915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005154467210319831,"score_gpt":0.2104835463366228,"score_spread":0.205329079126303,"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."}}