{"id":"W3194018435","doi":"10.5604/01.3001.0015.2377","title":"CLT – material for the measure of the future","year":2021,"lang":"en","type":"article","venue":"Annals of WULS Forestry and Wood Technology","topic":"Civil and Structural Engineering Research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cross laminated timber; Product (mathematics); Perpendicular; Laminated veneer lumber; Measure (data warehouse); Wood industry; Engineering; Structural engineering; Computer science; Materials science; Mathematics; Composite material; Geography; Forestry; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005240477,0.00189516,0.0006981023,0.007147548,0.002410029,0.006770161,0.00200514,0.003647536,0.1107955],"category_scores_gemma":[0.01666391,0.0004861474,0.001026515,0.004006235,0.002885288,0.008832845,0.00492844,0.004077654,0.04850287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003498584,"about_ca_system_score_gemma":0.004987608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003746237,"about_ca_topic_score_gemma":0.002680787,"domain_scores_codex":[0.9921229,0.001513386,0.0007585491,0.0006903089,0.004448696,0.000465999],"domain_scores_gemma":[0.990799,0.002029769,0.001022723,0.001067079,0.004422114,0.0006593251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001576462,0.0000704743,0.001135942,0.001289074,0.00003329539,0.0002078369,0.0004942016,0.001081145,0.001764425,0.3009896,0.5165845,0.1761919],"study_design_scores_gemma":[0.00001225462,0.00005484369,0.000796411,0.0005556204,0.00001101708,0.000163142,0.0001807699,0.0002007286,0.0003529211,0.01728436,0.9803566,0.00003123916],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.004316919,0.02069717,0.05012606,0.018891,0.02144327,0.000985065,0.01293004,0.002656556,0.8679539],"genre_scores_gemma":[0.1919334,0.041419,0.1175116,0.0176407,0.01318772,0.007202941,0.03401965,0.004338816,0.5727462],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1107955,"threshold_uncertainty_score":0.370648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01451385546393904,"score_gpt":0.2466251396744339,"score_spread":0.2321112842104948,"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."}}