{"id":"W4402646404","doi":"10.1007/s00466-024-02545-6","title":"An improved thermomechanical model for the prediction of stress and strain evolution in proximity to the melt pool in powder bed fusion additive manufacturing","year":2024,"lang":"en","type":"article","venue":"Computational Mechanics","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Strain (injury); Computational Science and Engineering; Fusion; Materials science; Stress (linguistics); Stress–strain curve; Composite material; Mathematics; Deformation (meteorology); Applied mathematics","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":[0.0002725514,0.000114998,0.0001108365,0.00008186288,0.00005488236,0.000045516,0.0001048265,0.0000623794,0.00000879456],"category_scores_gemma":[0.0000312123,0.00007852131,0.00002291426,0.00008162848,0.00001007586,0.0001521193,0.00003593502,0.0001173103,4.680909e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007054154,"about_ca_system_score_gemma":0.00003204581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001705047,"about_ca_topic_score_gemma":0.0001243589,"domain_scores_codex":[0.99932,0.00003236557,0.0002108573,0.0001839018,0.0001205709,0.0001323249],"domain_scores_gemma":[0.9995651,0.0002651343,0.00002455453,0.00007860122,0.0000397791,0.00002689335],"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":[0.00005188306,0.00002404977,0.0000013434,0.0001933204,0.00002043795,6.166027e-7,0.0009923539,0.9634762,0.008548112,0.008386255,0.00001321223,0.01829219],"study_design_scores_gemma":[0.0001665506,0.00006133116,0.001642588,0.0001067091,0.00001083641,0.000001350896,0.0001743288,0.9236715,0.02593499,0.04814978,0.000007364985,0.00007268019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3407907,0.00007353102,0.6572608,0.000107571,0.000168487,0.000562551,0.0009838927,0.00005035991,0.000002075547],"genre_scores_gemma":[0.9984925,0.0000176379,0.001109405,0.00002149383,0.00007292924,0.0001535258,0.0001100389,0.00002048096,0.000001975273],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6577018,"threshold_uncertainty_score":0.3202006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01418788554774776,"score_gpt":0.2365810920685973,"score_spread":0.2223932065208496,"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."}}