{"id":"W7081996317","doi":"10.11159/iccpe25.117","title":"Prediction of Tensile Modulus Of Polymeric Materials Combined With Molecular Dynamics And Deep Learning","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Tokyo","keywords":"Ultimate tensile strength; Molecular dynamics; Modulus; Deep learning; Deep drawing; Young's modulus; Polymer","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0002046922,0.0005909639,0.0003007975,0.0004001368,0.0001893347,0.0002519269,0.0003948358,0.0005998288,0.0006402478],"category_scores_gemma":[0.0007428001,0.0003177659,0.0003618454,0.0002900104,0.0002194916,0.0008359514,0.0002779724,0.0007112527,0.000187269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003973267,"about_ca_system_score_gemma":0.000538426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003242676,"about_ca_topic_score_gemma":0.004508833,"domain_scores_codex":[0.9999523,0.000006562491,0.00000278808,0.00001278177,0.0000190213,0.000006521794],"domain_scores_gemma":[0.9997812,0.00009309186,0.00004710145,0.0000197477,0.00004377749,0.00001520437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003602725,0.00006697467,0.001987139,0.00005204698,0.00002352104,0.00006473326,0.00001053864,0.9478005,0.01923876,0.001490514,0.000327082,0.02890209],"study_design_scores_gemma":[8.116107e-7,0.000005016105,0.0001217482,8.04293e-7,8.979933e-7,0.000002549022,4.427543e-7,0.9983822,0.001239824,0.0001926029,0.00005177591,0.000001288256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.473369,0.001146963,0.5188367,0.0005979349,0.00009647945,0.00006241538,0.0004395424,0.001201224,0.004249602],"genre_scores_gemma":[0.9458454,0.0005338835,0.05145379,0.00006016787,0.00003104252,0.00007078171,0.0002957397,0.00005484222,0.001654409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003242676,"threshold_uncertainty_score":0.006447613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003193406395315104,"score_gpt":0.1668585756610928,"score_spread":0.1636651692657777,"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."}}