{"id":"W2073628521","doi":"10.1071/wf04054","title":"Calibrating the Fine Fuel Moisture Code for grass ignition potential in Sumatra, Indonesia","year":2005,"lang":"en","type":"article","venue":"International Journal of Wildland Fire","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Forest Service","funders":"Universitas Riau","keywords":"Water content; Environmental science; Ignition system; Moisture; Dryness; Fire regime; Mediterranean climate; Meteorology; Atmospheric sciences; Geography; Ecology; Ecosystem; Biology; Geology; Archaeology; Engineering","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":[0.0004336537,0.0003047074,0.0002574781,0.00062445,0.000240832,0.0004072758,0.0003083772,0.0001618034,0.0003888067],"category_scores_gemma":[0.00122012,0.0001982812,0.000123241,0.0005123499,0.0001918477,0.0002918719,0.0002786947,0.0002359992,0.000211925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006389341,"about_ca_system_score_gemma":0.000298575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02988232,"about_ca_topic_score_gemma":0.07227679,"domain_scores_codex":[0.9997754,0.0000475351,0.00002151589,0.00006433493,0.00007081062,0.00002048206],"domain_scores_gemma":[0.9995409,0.0001001655,0.00009395782,0.00005724169,0.0001472244,0.00006043333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000196989,0.0002564736,0.9311574,0.00003432717,0.00004463985,0.0001831037,0.0003995349,0.005177773,0.02351593,0.00005824361,0.0001894797,0.03878614],"study_design_scores_gemma":[0.000006941207,0.00007287032,0.9800962,0.000004867851,0.00001267298,0.00008103381,0.0002412942,0.01468466,0.00448787,0.00004677134,0.0002561745,0.000008665428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981412,0.0000148606,0.001055079,0.000004872292,0.000002026136,0.0000208224,0.0001167778,0.000020784,0.0006234646],"genre_scores_gemma":[0.9971355,0.00001641173,0.002402602,0.000005594209,0.000001026439,0.00001919657,0.0002334078,0.000006966588,0.0001792563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02988232,"threshold_uncertainty_score":0.05941677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006661219025036442,"score_gpt":0.2318356662079265,"score_spread":0.22517444718289,"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."}}