{"id":"W2001667852","doi":"10.1080/07373930008917809","title":"MODELING VACUUM-CONTACT DRYING OF WOOD: THE WATER POTENTIAL APPROACH","year":2000,"lang":"en","type":"article","venue":"Drying Technology","topic":"Textile materials and evaluations","field":"Materials Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Ministère des Ressources naturelles et des Forêts; Centre de Géomatique du Québec","funders":"","keywords":"Wood drying; Vacuum drying; Pulp and paper industry; Materials science; Environmental science; Process engineering; Composite material; Chemistry; Moisture; Engineering; Chromatography; 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":[0.0002020861,0.0004171569,0.0004910649,0.0003115037,0.0002612842,0.0005504484,0.0009644149,0.0008221313,0.001025134],"category_scores_gemma":[0.0003422486,0.0003273985,0.0005241396,0.0002527741,0.0003784313,0.0008692597,0.0004230326,0.0004292042,0.0002615509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003836124,"about_ca_system_score_gemma":0.0004216672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002016677,"about_ca_topic_score_gemma":0.001423278,"domain_scores_codex":[0.9999083,0.00001863824,0.000004438045,0.00001713355,0.00003768272,0.00001379555],"domain_scores_gemma":[0.9999182,0.00004202629,0.00001212899,0.000007899497,0.00001326149,0.000006476871],"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":[0.00002601169,0.0000528027,0.0004772204,0.0001614771,0.00001546763,0.0001742527,0.00006563731,0.9309409,0.03950152,0.01465415,0.0002053751,0.01372517],"study_design_scores_gemma":[0.00000371027,0.00001882524,0.0001610765,0.000004452901,0.000003468482,0.00004307489,0.000009511814,0.9932528,0.003886122,0.001864903,0.0007449537,0.00000701594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1207273,0.001022269,0.8714046,0.0001179722,0.0000372707,0.00008012373,0.00007709194,0.0002046328,0.00632872],"genre_scores_gemma":[0.9173692,0.001649648,0.07211697,0.00005290578,0.00002493652,0.000218903,0.0001228877,0.00009298953,0.00835157],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002016677,"threshold_uncertainty_score":0.004009843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01751299213928763,"score_gpt":0.2410126890015509,"score_spread":0.2234996968622632,"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."}}