{"id":"W4382775441","doi":"10.3390/ma16134693","title":"A Novel Approach for Analyzing the Effects of Almen Intensity on the Residual Stress and Hardness of Shot-Peened (TiB + TiC)/Ti–6Al–4V Composite: Deep Learning","year":2023,"lang":"en","type":"article","venue":"Materials","topic":"Titanium Alloys Microstructure and Properties","field":"Materials Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"RUDN University; Karabük Üniversitesi; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Residual stress; Materials science; Peening; Composite number; Shot peening; Shot (pellet); Composite material; Intensity (physics); Indentation hardness; Metallurgy; Microstructure; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001008173,0.0001704979,0.0004222196,0.00005575366,0.0002500007,0.000132535,0.0003231334,0.00007262322,0.00003437177],"category_scores_gemma":[0.0003279989,0.00009042531,0.00004595717,0.0001264872,0.0002382628,0.00006977854,0.0002178144,0.00006828627,0.000004431771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000129809,"about_ca_system_score_gemma":0.00001571653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001586943,"about_ca_topic_score_gemma":0.000007520505,"domain_scores_codex":[0.9987564,0.0002135172,0.0003355611,0.0002589169,0.0001798994,0.0002557196],"domain_scores_gemma":[0.9988449,0.0004980629,0.0002309931,0.0002819106,0.0001170908,0.00002701622],"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":[0.0004385826,0.00002133354,0.0003509571,0.0006301252,0.00004073302,8.027182e-7,0.002060876,0.0001207622,0.9958165,0.0003149518,0.0001092252,0.00009511964],"study_design_scores_gemma":[0.0003655911,0.0001818183,0.009317619,0.0001405881,0.00006906967,0.000004463123,0.000609732,0.00007158623,0.9889825,0.00009892751,0.00004535714,0.0001127429],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981923,0.0001189945,0.0002807521,0.0001530546,0.0004490994,0.0005853511,0.0001231204,0.00004504618,0.00005232323],"genre_scores_gemma":[0.9990395,0.00001809107,0.0005640446,0.00006046376,0.00009456639,0.00004619909,0.00003520323,0.00002278983,0.000119129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008966662,"threshold_uncertainty_score":0.3687437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0253605532380761,"score_gpt":0.24132008897569,"score_spread":0.215959535737614,"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."}}