{"id":"W1994768374","doi":"10.1080/11263504.2011.638332","title":"Pre-logging carbon accounts in old-growth forests, via allometry: An example of mixed-forest in Tasmania, Australia","year":2011,"lang":"en","type":"article","venue":"Plant Biosystems - An International Journal Dealing with all Aspects of Plant Biology","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Parks and Wilderness Society","funders":"","keywords":"Understory; Clearcutting; Biomass (ecology); Environmental science; Forestry; Logging; Rainforest; Tree allometry; Old-growth forest; Carbon sequestration; Eucalyptus; Agroforestry; Ecology; Biology; Geography; Carbon dioxide; Canopy; Biomass partitioning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0005067228,0.0001539277,0.0002041117,0.0006087408,0.0007486934,0.0006321893,0.0004883955,0.0001677393,0.0008466682],"category_scores_gemma":[0.001223476,0.0001422136,0.0001656166,0.0009030944,0.0005871681,0.0005113052,0.0004946643,0.0002322334,0.00008900994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001401436,"about_ca_system_score_gemma":0.0007456345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3401076,"about_ca_topic_score_gemma":0.6223078,"domain_scores_codex":[0.9998419,0.00005029088,0.00001181988,0.00003810762,0.00002391747,0.0000339322],"domain_scores_gemma":[0.9994042,0.00009465019,0.0001256816,0.00006293312,0.0002121788,0.0001003848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001592004,0.00005762853,0.9752917,0.00002939005,0.000105579,0.0004390572,0.002980957,0.00161239,0.003525686,0.001049145,0.0003007836,0.01444845],"study_design_scores_gemma":[0.0000018195,0.00001220125,0.9966577,0.000004092477,0.00001187022,0.00005201666,0.0005243433,0.002224856,0.0001037536,0.0001773653,0.0002260057,0.000004076856],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990402,0.00006153381,0.0001382764,0.0000368957,9.982828e-7,0.000003323946,0.0000598274,0.000003240926,0.0006557381],"genre_scores_gemma":[0.9996071,0.00001261817,0.0001578358,0.000006164872,8.079191e-7,0.000001022402,0.00003370896,0.000001875686,0.000178826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3401076,"threshold_uncertainty_score":0.6762558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0311501052159849,"score_gpt":0.2494395284326739,"score_spread":0.218289423216689,"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."}}