{"id":"W2012040847","doi":"10.1016/j.apm.2011.04.011","title":"Multiphysics modeling of vacuum drying of wood","year":2011,"lang":"en","type":"article","venue":"Applied Mathematical Modelling","topic":"Textile materials and evaluations","field":"Materials Science","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Multiphysics; Wood drying; Vacuum drying; Mechanical engineering; Materials science; Engineering; Composite material; Physics; Finite element method; Structural engineering; Thermodynamics; Freeze-drying","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":[0.0003449522,0.0003664276,0.0005289672,0.0003958621,0.0004258801,0.0007536199,0.0006097366,0.0008986986,0.001130896],"category_scores_gemma":[0.0008241794,0.0003727779,0.0006329275,0.0003684382,0.0005841313,0.0007878198,0.0003678467,0.0004815446,0.0001655588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006373792,"about_ca_system_score_gemma":0.0005801572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004767302,"about_ca_topic_score_gemma":0.002393294,"domain_scores_codex":[0.9998369,0.00003700296,0.000008148559,0.00002553288,0.00006585704,0.00002649784],"domain_scores_gemma":[0.9997833,0.0001281467,0.0000234354,0.00002023239,0.00003361192,0.00001118335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002588552,0.00004586469,0.0002897464,0.00004748881,0.000008344635,0.00005356386,0.00005344936,0.9797028,0.01111182,0.004760773,0.00009839132,0.003801842],"study_design_scores_gemma":[0.000002495451,0.000008253916,0.0002652199,0.000002224289,0.000001882293,0.00001304318,0.00001078249,0.9975187,0.001408775,0.0006108772,0.0001541416,0.000003764792],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5809429,0.001877294,0.3859333,0.0005524925,0.0001381756,0.0001127133,0.0001671799,0.000215622,0.03006026],"genre_scores_gemma":[0.9859482,0.0005204286,0.007313889,0.00004972872,0.00001921146,0.00004875986,0.00005395423,0.00004040461,0.006005395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004767302,"threshold_uncertainty_score":0.009479105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1227287538664482,"score_gpt":0.2622696981122484,"score_spread":0.1395409442458002,"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."}}