{"id":"W2355466462","doi":"","title":"Study on Assessment of Beijing Forest Fire Danger","year":2006,"lang":"en","type":"article","venue":"Fire Safety Science","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Beijing; Environmental science; Rating system; Meteorology; Noon; Atmospheric sciences; Geography; China; Geology","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":[0.000949654,0.0002740123,0.0002596774,0.001278648,0.000282474,0.0004162327,0.0001774559,0.0001754852,0.001331852],"category_scores_gemma":[0.001577016,0.0001145802,0.000195717,0.001428215,0.0001384001,0.0006412052,0.000313317,0.0001619204,0.0001197257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009141276,"about_ca_system_score_gemma":0.0003452122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01668318,"about_ca_topic_score_gemma":0.02209142,"domain_scores_codex":[0.9994591,0.0001223652,0.00003963043,0.0000564127,0.0002551492,0.00006723707],"domain_scores_gemma":[0.9992562,0.0002025549,0.0001421264,0.00004812504,0.0002577192,0.00009323136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003025453,0.00010099,0.8734087,0.0001730655,0.000100513,0.0008618042,0.002685744,0.01076857,0.007945925,0.00159234,0.0009189089,0.1011409],"study_design_scores_gemma":[0.000008401652,0.0002239997,0.9717489,0.00001699331,0.00004428172,0.0003458734,0.001360645,0.02113997,0.00256692,0.0004500826,0.002070462,0.00002339182],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955496,0.0001123524,0.0007736878,0.00003737902,0.000002713552,0.00001795438,0.00007215185,0.000009985944,0.003424289],"genre_scores_gemma":[0.998725,0.00008396786,0.0004151683,0.00000556832,0.000002703568,0.000007384589,0.0001153663,0.00000187889,0.0006428634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01668318,"threshold_uncertainty_score":0.03317219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008507043331644601,"score_gpt":0.2586176975798994,"score_spread":0.2501106542482548,"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."}}