{"id":"W2084043503","doi":"10.1515/hf.2009.111","title":"Characterizing hydro-thermal compression behavior of aspen wood strands","year":2009,"lang":"en","type":"article","venue":"Holzforschung","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"FPInnovations; University of British Columbia","funders":"FPInnovations","keywords":"Materials science; Moisture; Water content; Consolidation (business); Composite material; Oriented strand board; Compression (physics); Hot press; Green wood; Pressing; Softwood; Solid wood; Wood drying; Geotechnical engineering; Geology","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":[0.00004545151,0.0001414747,0.0001864625,0.00005747115,0.0000423237,0.00002052539,0.0001077349,0.00006536915,0.0001133932],"category_scores_gemma":[0.000001619984,0.0001183745,0.0000666613,0.00006891869,0.00001507598,0.0002136284,0.0000110857,0.0001014196,0.00002541494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000157552,"about_ca_system_score_gemma":0.000004754958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000548747,"about_ca_topic_score_gemma":0.000001170073,"domain_scores_codex":[0.9993827,0.00001102806,0.0001901977,0.00009889684,0.0001198929,0.000197253],"domain_scores_gemma":[0.9997382,0.000009058375,0.00003020014,0.0001590281,0.00001331044,0.00005015767],"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":[0.00003499545,0.00009847517,0.004457157,0.00004010967,0.00003910092,0.00001946564,0.000700088,0.0004335264,0.9136704,0.00005002911,0.00007027076,0.08038634],"study_design_scores_gemma":[0.0007678241,0.0002022425,0.1845599,0.0001252955,0.00007303234,0.000008170436,0.00004551904,0.001311473,0.8120518,0.00002310612,0.0005809289,0.0002507264],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889255,0.0007393725,0.00002742139,0.00002616985,0.0001220475,0.0001467755,0.000008100941,0.0001788277,0.00982576],"genre_scores_gemma":[0.999405,0.0000489485,0.000275889,0.00001529359,0.00007054165,0.00001050625,0.00002516856,0.00001910252,0.0001296101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1801027,"threshold_uncertainty_score":0.4827173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01541828638853069,"score_gpt":0.218027040323044,"score_spread":0.2026087539345133,"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."}}