{"id":"W4407028692","doi":"10.2139/ssrn.5119220","title":"Investigating the Shear and Thermal Properties of Additively Manufactured Wood-Pla Biocomposites","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Materials science; Shear (geology); Composite material; Thermal; Polymer science; Pulp and paper industry; Engineering; Thermodynamics; Physics","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":[0.000350022,0.000363969,0.0001696293,0.0003146602,0.0001343116,0.0002978309,0.0001707909,0.0002598173,0.00194325],"category_scores_gemma":[0.0004794272,0.0001877958,0.0002378107,0.0003563167,0.0002742274,0.0003906134,0.0001600254,0.0004385279,0.0003309715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001368325,"about_ca_system_score_gemma":0.0001289514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003890499,"about_ca_topic_score_gemma":0.0006838881,"domain_scores_codex":[0.999762,0.00002661463,0.00001930475,0.0000504472,0.00009856492,0.00004309027],"domain_scores_gemma":[0.9997223,0.00007975665,0.00009278318,0.00002374385,0.00006158099,0.00001970027],"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":[0.0001201414,0.00001273212,0.000417137,0.00003141338,0.000005752956,0.00003280808,0.0000419141,0.0002109149,0.9978234,0.00005724734,0.00001178594,0.001234862],"study_design_scores_gemma":[0.000001601695,0.0001154734,0.0024995,0.000003147487,0.00001156653,0.00002221104,0.000026403,0.0005879426,0.996437,0.00001262064,0.0002795605,0.000003103869],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970425,0.0006262392,0.001437847,0.00001132353,0.00001391979,0.000007202891,0.00007760087,0.00001583057,0.0007676232],"genre_scores_gemma":[0.9972921,0.0003191891,0.001043622,0.00001422948,0.000005228088,0.00001011848,0.00008936248,0.000016671,0.001209478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00194325,"threshold_uncertainty_score":0.00650084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204678828400137,"score_gpt":0.207251909539971,"score_spread":0.1952051212559696,"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."}}