{"id":"W2057170127","doi":"10.1007/s00226-015-0717-9","title":"Study of the elastic behaviour of wood–plastic composites at cold temperatures using artificial neural networks","year":2015,"lang":"en","type":"article","venue":"Wood Science and Technology","topic":"Natural Fiber Reinforced Composites","field":"Materials Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue; Natural Sciences and Engineering Research Council; Hydro-Québec; Université du Québec à Chicoutimi","funders":"","keywords":"Composite material; Materials science; High-density polyethylene; Wood flour; Low-density polyethylene; Composite number; Polyethylene; Wood-plastic composite; Viscoelasticity","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001687414,0.0001986379,0.0001725459,0.0002282171,0.0002076741,0.0001593843,0.0001877187,0.0002402037,0.0006302174],"category_scores_gemma":[0.0003601142,0.000154007,0.0002178901,0.0002004121,0.0003080836,0.0002826225,0.000112205,0.0002907025,0.00006761777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000171335,"about_ca_system_score_gemma":0.0001092003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001385274,"about_ca_topic_score_gemma":0.001911874,"domain_scores_codex":[0.999941,0.000008408913,0.000002633315,0.00001193492,0.00002428628,0.0000117665],"domain_scores_gemma":[0.9997818,0.0001167742,0.00002923716,0.00001443628,0.00004631546,0.00001141622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006380933,0.0002380755,0.00521077,0.0002039554,0.00005434857,0.0003269774,0.0001661475,0.3693312,0.603269,0.001698576,0.0002157293,0.01864704],"study_design_scores_gemma":[0.000006082183,0.0001953295,0.007876529,0.000007102023,0.00001578191,0.00003963828,0.00004354659,0.8867796,0.1045264,0.0002220117,0.0002752854,0.000012706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942551,0.0001396759,0.004238935,0.0000323457,0.00001375085,0.000004421277,0.00001748692,0.00001275835,0.001285463],"genre_scores_gemma":[0.9986476,0.00004839586,0.0007401163,0.000002498477,0.000002458773,0.000002387404,0.00001198896,0.000002521404,0.0005418542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001385274,"threshold_uncertainty_score":0.00275439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02251277724065548,"score_gpt":0.2623658605110205,"score_spread":0.239853083270365,"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."}}