{"id":"W1991663476","doi":"10.2298/tsci140109055k","title":"Computational analysis of heat and mass transfer during microwave drying of timber","year":2014,"lang":"en","type":"article","venue":"Thermal Science","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Microwave; Mass transfer; Materials science; Microwave heating; Water content; Microwave irradiation; Heat transfer; Moisture; Finite element method; Microwave oven; Internal heating; Process (computing); Sample (material); Nuclear engineering; Environmental science; Mechanics; Thermodynamics; Composite material; Computer science; Geotechnical engineering; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009212492,0.00003993093,0.00009167076,0.00008571987,0.00003244878,0.000007437278,0.00005384076,0.000009231827,0.00002900416],"category_scores_gemma":[0.000001723691,0.00003108843,0.00002235759,0.0002730486,0.0001282878,0.00007939428,0.000006941616,0.00001621519,9.776488e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000739804,"about_ca_system_score_gemma":0.000003909462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001339262,"about_ca_topic_score_gemma":0.000002918998,"domain_scores_codex":[0.9996814,0.000006144427,0.00007657846,0.00006009913,0.00009765843,0.00007810711],"domain_scores_gemma":[0.9998944,0.00001716177,0.000004320235,0.00004630115,0.00001758909,0.00002016975],"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":[0.00000373262,0.000003347812,0.009659264,0.00001574798,0.0000499391,1.1576e-7,0.0006667001,0.3640876,0.6247299,0.00007265867,1.371664e-7,0.0007108371],"study_design_scores_gemma":[0.000135109,0.00001612367,0.2004508,0.000008898251,0.00007972958,4.532319e-7,0.00002234436,0.3708794,0.4283059,0.00004398204,0.000002220541,0.00005513358],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952071,0.00008593535,0.002081704,0.00000795707,0.00001220724,0.00002085684,0.000001919698,0.00001275194,0.002569554],"genre_scores_gemma":[0.9993252,0.000003171646,0.000648555,0.000002302895,0.000004165958,6.278601e-7,6.583681e-7,0.000002565848,0.0000127594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1964241,"threshold_uncertainty_score":0.1267749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007525038586134447,"score_gpt":0.1898756972449731,"score_spread":0.1823506586588386,"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."}}