{"id":"W2414055614","doi":"","title":"Understanding effects of drying methods on wood mechanical properties at ultra and cellular levels","year":2016,"lang":"en","type":"article","venue":"Wood and Fiber Science (Society of Wood Science and Technology)","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; FPInnovations","keywords":"Nanoindentation; Wood drying; Kiln; Composite material; Materials science; Vacuum drying; Softwood; Oriented strand board; Water content; Young's modulus; Flexural strength; Moisture; Equilibrium moisture content; Humidity; Pulp and paper industry; Freeze-drying; Chemistry; Metallurgy; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001014642,0.0002108233,0.0003141437,0.000284251,0.0005387737,0.00005895177,0.0003520584,0.0001486722,0.00000428433],"category_scores_gemma":[0.0001384326,0.0001295168,0.00004284386,0.001200357,0.004539252,0.0005319468,0.0002306846,0.0001260498,0.000001588804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001156087,"about_ca_system_score_gemma":0.00007541425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003504401,"about_ca_topic_score_gemma":0.000001117106,"domain_scores_codex":[0.9983694,0.00001584437,0.0002272375,0.0004897525,0.0004239199,0.0004738685],"domain_scores_gemma":[0.9993341,0.0001158134,0.00007066257,0.0002684885,0.00009223031,0.0001186869],"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":[0.000004597199,0.00001895433,0.0001839486,0.0001231288,0.0000215473,7.172083e-7,0.0007636499,0.000001191022,0.9798226,0.002244362,0.00001875135,0.01679654],"study_design_scores_gemma":[0.0004761924,0.0004030819,0.0001251486,0.0003227926,0.0000255246,0.00001048112,0.0007652189,0.0004750679,0.9949122,0.002193013,0.00009906689,0.0001921762],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958871,0.001491199,0.001062458,0.0006917925,0.0001007746,0.0002249665,0.000003344771,0.0001278762,0.0004104928],"genre_scores_gemma":[0.9924954,0.0004787472,0.006892563,0.00001980341,0.000008616189,0.00001107165,7.293769e-8,0.00001081935,0.00008297752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01660437,"threshold_uncertainty_score":0.9981698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04903069739147076,"score_gpt":0.2446257414464869,"score_spread":0.1955950440550162,"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."}}