{"id":"W4296977943","doi":"10.48550/arxiv.1612.02382","title":"A Model-Based Approach to Wildland Fire Reconstruction Using Sediment\\n Charcoal Records","year":2016,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Charcoal; Fire history; Multivariate statistics; Sediment; Environmental science; Univariate; Physical geography; Hydrology (agriculture); Geology; Geography; Climate change; Statistics; Geomorphology; Oceanography; Mathematics","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":[0.001636765,0.0006640764,0.0009776647,0.001317292,0.0006117046,0.001659375,0.001800692,0.001231255,0.001648525],"category_scores_gemma":[0.00389279,0.0009683209,0.001469249,0.001009263,0.0007337225,0.0009543152,0.001023091,0.001196948,0.0002784841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001651908,"about_ca_system_score_gemma":0.001748471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02546006,"about_ca_topic_score_gemma":0.0314846,"domain_scores_codex":[0.9996325,0.0001409672,0.00002088476,0.0001163222,0.00005188448,0.00003752935],"domain_scores_gemma":[0.998664,0.0008427388,0.0002119942,0.00009015002,0.0001312003,0.00005989763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001248205,0.00001834365,0.001125328,0.0000129799,0.00005074204,0.00002480668,0.000020094,0.98446,0.0002271688,0.007070075,0.0001355132,0.006842567],"study_design_scores_gemma":[0.000002248219,0.000003809454,0.0001374703,0.000002299406,0.000005342207,0.000005154132,0.000003703401,0.9962676,0.00005228804,0.003419539,0.00009642305,0.000004068232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03705706,0.0001747242,0.9606079,0.0002698998,0.0000200781,0.00003118607,0.0002504405,0.0003209513,0.001267675],"genre_scores_gemma":[0.74367,0.0003508673,0.2506447,0.0001094178,0.00009105744,0.0002223021,0.0007240445,0.0001793247,0.004008368],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02546006,"threshold_uncertainty_score":0.05062371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05182734547530732,"score_gpt":0.1778107293482635,"score_spread":0.1259833838729562,"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."}}