{"id":"W2361654822","doi":"","title":"An Estimation of Heating Rates in Sub-Alpine Fir Lumber","year":2005,"lang":"en","type":"article","venue":"Wood and Fiber Science (Society of Wood Science and Technology)","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Forest Service; Natural Resources Canada; U.S. Forest Service; FPInnovations","keywords":"Kiln; Water content; Wood drying; Environmental science; Moisture; Energy density; Abies lasiocarpa; Green wood; Wet-bulb temperature; Pulp and paper industry; Mass transfer; Materials science; Waste management; Meteorology; Composite material; Montane ecology; Engineering; Humidity; Thermodynamics; Geotechnical engineering; Geography; Engineering physics; Physics; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0001708985,0.0003491246,0.0001990576,0.0003408964,0.00008112755,0.0001751114,0.0001364381,0.000208724,0.0005317304],"category_scores_gemma":[0.0005090066,0.0001480571,0.0001152457,0.0001452552,0.00005949141,0.0002048351,0.00005579903,0.0001514062,0.0002273449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000147238,"about_ca_system_score_gemma":0.00007641467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001901429,"about_ca_topic_score_gemma":0.002431557,"domain_scores_codex":[0.9999316,0.000009718226,0.000002810604,0.00002722221,0.00002105578,0.00000749531],"domain_scores_gemma":[0.9997541,0.0001351764,0.00004621138,0.00001979487,0.00003403286,0.00001057625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008550859,0.0001048126,0.1057159,0.0002202939,0.00004717685,0.0001285029,0.0002485093,0.02364795,0.7525723,0.0001156035,0.0001341367,0.1162097],"study_design_scores_gemma":[0.0000145609,0.0004427549,0.3072119,0.00001520629,0.00006546362,0.0001693417,0.00008211455,0.1369705,0.5537376,0.00007533006,0.001186789,0.00002838536],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863521,0.0002002809,0.01261812,0.000004708804,0.000002571584,0.000009345091,0.0001258099,0.0001702486,0.0005167471],"genre_scores_gemma":[0.9936461,0.0001147676,0.005722877,0.000002490221,0.000002175384,0.000007956042,0.0001081534,0.00001654009,0.0003789678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001901429,"threshold_uncertainty_score":0.003780782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007513601234339831,"score_gpt":0.2274351423153431,"score_spread":0.2199215410810032,"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."}}