{"id":"W4382238648","doi":"10.1016/j.jmrt.2023.05.088","title":"Towards optimization of polymer filament tensile test for material extrusion additive manufacturing process","year":2023,"lang":"en","type":"article","venue":"Journal of Materials Research and Technology","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; National Research Council Canada; Toronto Metropolitan University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Ultimate tensile strength; Extrusion; Extensometer; Acrylonitrile butadiene styrene; Fused filament fabrication; Tensile testing; Protein filament; Composite material; Charpy impact test; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006228181,0.0001215345,0.0003142017,0.000959628,0.00009337159,0.00004157937,0.0002433998,0.0002055008,0.00007600711],"category_scores_gemma":[0.000541083,0.00009889542,0.00002609509,0.0002582968,0.0002219963,0.00009619733,0.0001664143,0.0001913204,0.000002352597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003536,"about_ca_system_score_gemma":0.00003410725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003304595,"about_ca_topic_score_gemma":3.763793e-7,"domain_scores_codex":[0.9989064,0.00002198239,0.0003898934,0.0001305608,0.0002132615,0.0003378856],"domain_scores_gemma":[0.9992017,0.0001731211,0.0001386229,0.0001334598,0.0003160981,0.00003705546],"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":[0.0002089456,0.0000602742,0.00002838819,0.0005829764,0.00009712486,0.00004101798,0.0001013919,0.001626319,0.9525629,0.0004828532,0.002163788,0.04204408],"study_design_scores_gemma":[0.0003315537,0.000543929,0.0001229371,0.0001592682,0.000006298243,0.00003979585,0.0004136214,0.0003099607,0.9910846,0.006547086,0.0003531133,0.00008785151],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973728,0.00007650127,0.001177341,0.0003971638,0.0002602526,0.000217982,0.0001762292,0.0002649968,0.00005673809],"genre_scores_gemma":[0.9977381,0.0005226965,0.001501488,0.000001524536,0.0001098722,0.00003816867,0.00001622818,0.00002681158,0.00004516586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04195623,"threshold_uncertainty_score":0.4032838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03140215106497938,"score_gpt":0.3072361672592388,"score_spread":0.2758340161942594,"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."}}