{"id":"W4293052848","doi":"10.1007/s00107-022-01837-z","title":"Technical properties improvement of engineered flooring through hardening by acrylate surface impregnation and in-situ electron beam polymerization","year":2022,"lang":"en","type":"article","venue":"European Journal of Wood and Wood Products","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Natural Sciences and Engineering Research Council of Canada","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Brinell scale; Materials science; Hardwood; Hardness; Composite material; Polymerization; Acrylate; Surface modification; Monomer; Ultimate tensile strength; Chemical engineering; Polymer","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001064076,0.000408082,0.000181334,0.0002548015,0.0001179815,0.0002832594,0.0001646475,0.00020357,0.001027646],"category_scores_gemma":[0.0001384085,0.0001842569,0.0002336495,0.0001744171,0.0001418031,0.000188961,0.0001755563,0.0003787141,0.0001892478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001067044,"about_ca_system_score_gemma":0.0001680392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003571943,"about_ca_topic_score_gemma":0.001314177,"domain_scores_codex":[0.9999113,0.000004592385,0.000005527558,0.00001726585,0.00003628262,0.00002508769],"domain_scores_gemma":[0.9998823,0.00001796034,0.00003808344,0.00001697999,0.00002394101,0.0000205469],"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":[0.00001631744,0.00001349859,0.0001608244,0.00003119011,0.000002805581,0.00007248259,0.00001784987,0.0003588181,0.9966208,0.00005519715,0.00001420076,0.002636111],"study_design_scores_gemma":[0.000001971832,0.00008387221,0.003231912,0.000002442936,0.00001186419,0.00005803184,0.00001426858,0.0009077981,0.9949981,0.00001812987,0.0006668548,0.000004671939],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901881,0.0003474118,0.007507915,0.00001392513,0.00002265827,0.000009345751,0.0000509225,0.0001031653,0.001756701],"genre_scores_gemma":[0.9936525,0.0001707996,0.004033688,0.000009920118,0.000002947432,0.000004561686,0.00005322011,0.00003086763,0.00204153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001027646,"threshold_uncertainty_score":0.003437817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00880027539390188,"score_gpt":0.1774680866268208,"score_spread":0.1686678112329189,"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."}}