{"id":"W2560976564","doi":"10.1080/20426445.2016.1204514","title":"Reducing the thickness swelling of a model wood composite by creating a three-dimensional adhesive network","year":2016,"lang":"en","type":"article","venue":"International Wood Products Journal","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"China Scholarship Council; FPInnovations; Bangor University; Australian National University","keywords":"Swelling; Composite material; Adhesive; Materials science; Composite number; Polyurethane; Veneer; Layer (electronics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004268692,0.0002073829,0.0002062201,0.00007450236,0.0002421002,0.00008860482,0.000377564,0.00005763112,0.00007066815],"category_scores_gemma":[0.00008477762,0.0001141593,0.0000931807,0.0001299024,0.00007330325,0.0003509097,0.00006361973,0.0002883461,0.00001711901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001003485,"about_ca_system_score_gemma":0.00006444802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000109179,"about_ca_topic_score_gemma":0.000004212883,"domain_scores_codex":[0.9985465,0.00004659113,0.0004535998,0.000194468,0.0004716391,0.0002871451],"domain_scores_gemma":[0.9990343,0.0001752658,0.0001863388,0.0001804694,0.0003617105,0.00006190503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002459373,0.0001211459,0.001595712,0.00004131506,0.001365892,0.00002139178,0.001389768,0.679963,0.2773044,0.000842401,0.01805603,0.01905303],"study_design_scores_gemma":[0.004431399,0.0004061377,0.001594907,0.00434942,0.0004445557,0.001912832,0.0001740626,0.40339,0.5523154,0.02329478,0.006259955,0.00142654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9722919,0.006732317,0.009469778,0.006085237,0.001876832,0.0002628485,0.00004782197,0.0001149393,0.003118304],"genre_scores_gemma":[0.9929228,0.0001520101,0.005037189,0.0000540227,0.001073072,0.00001138421,0.000007329576,0.0000391048,0.0007030174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.276573,"threshold_uncertainty_score":0.465528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01760793292057767,"score_gpt":0.2205788039799687,"score_spread":0.202970871059391,"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."}}