{"id":"W3125427163","doi":"10.20944/preprints201804.0194.v1","title":"The 2017 North Bay and Southern California Fires: A Case Study","year":2018,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bay; Environmental science; Extreme weather; Climatology; Precipitation; Geography; Climate change; Oceanography; Meteorology; Geology; Archaeology","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":["insufficient_payload"],"category_scores_codex":[0.001932439,0.0004982632,0.0004350322,0.00003958046,0.0007286982,0.000113932,0.001066433,0.0002285931,0.001089849],"category_scores_gemma":[0.0003563308,0.0003618292,0.0001279876,0.0001185453,0.0004812069,0.00007687119,0.006374425,0.0007675405,0.02285045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002618754,"about_ca_system_score_gemma":0.00004077114,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02094647,"about_ca_topic_score_gemma":0.04781632,"domain_scores_codex":[0.9963275,0.0005626716,0.0005633888,0.001413868,0.0005813504,0.0005512689],"domain_scores_gemma":[0.9965596,0.0002735638,0.0004151588,0.002461047,0.00002826244,0.0002623261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002739729,0.0001689106,0.9911733,0.00004798376,0.00009592015,0.0006965958,0.00631505,0.0001016195,0.00005522163,2.036273e-7,0.00025514,0.001062675],"study_design_scores_gemma":[0.0005950971,0.000110258,0.9769691,0.00009008979,0.0001389468,0.0007767444,0.002753706,0.003756241,0.0001191747,0.0001064435,0.01380328,0.000780987],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994256,0.00007670074,0.000011514,0.00009400282,0.000608853,0.002335152,0.0001612272,0.0001476844,0.002308819],"genre_scores_gemma":[0.9978632,0.00003157403,0.00002431519,0.00004666352,0.0002025618,0.0004126697,0.000008821902,0.00006235957,0.001347811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02686985,"threshold_uncertainty_score":0.9998834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05482725964150426,"score_gpt":0.2988226614613415,"score_spread":0.2439954018198373,"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."}}