{"id":"W6939236362","doi":"10.60692/kwzes-z2522","title":"Development of a Global Fire Weather Database","year":2015,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Natural Resources Canada; Canadian Forest Service","funders":"","keywords":"Precipitation; Latitude; Southeast asia; Global change; Data set","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002398674,0.0005390176,0.0005492056,0.004046486,0.0006713811,0.001229689,0.001560949,0.0004097303,0.00708439],"category_scores_gemma":[0.003722463,0.0003040725,0.0004449789,0.004393538,0.0001326677,0.001630677,0.001147883,0.0007876997,0.004357613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001448599,"about_ca_system_score_gemma":0.003215229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08676176,"about_ca_topic_score_gemma":0.0491265,"domain_scores_codex":[0.9991134,0.00008186378,0.0001977727,0.0002298946,0.000312026,0.00006495886],"domain_scores_gemma":[0.9964018,0.0002779103,0.0002117101,0.0008331383,0.001934961,0.0003405612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005678597,0.0004885484,0.1078376,0.0006980665,0.0002589127,0.0004221417,0.0005653601,0.03066855,0.008630525,0.01043617,0.4003647,0.4390616],"study_design_scores_gemma":[0.0004768798,0.000192233,0.2011576,0.0003141581,0.0002018945,0.0002868342,0.000619351,0.1185471,0.02254528,0.003781835,0.6516786,0.0001983437],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.04964816,0.0002529214,0.07325021,0.0005275373,0.0001973949,0.001537063,0.8429593,0.01277699,0.01885032],"genre_scores_gemma":[0.03627047,0.0001297167,0.05945773,0.00007442356,0.00002341658,0.0006617289,0.9009205,0.000360413,0.002101635],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.08676176,"threshold_uncertainty_score":0.1725135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04845507827090964,"score_gpt":0.211779428291788,"score_spread":0.1633243500208784,"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."}}