{"id":"W4411021752","doi":"10.1016/j.matlet.2025.138872","title":"Improving superelasticity of a laser powder bed-fused Ti-Zr-Nb alloy via the ingot composition adjustments","year":2025,"lang":"en","type":"article","venue":"Materials Letters","topic":"Titanium Alloys Microstructure and Properties","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"Russian Science Foundation","keywords":"Materials science; Ingot; Pseudoelasticity; Alloy; Metallurgy; Shape-memory alloy; Microstructure; Martensite","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":[0.0001195872,0.0001616418,0.0002257297,0.0001494001,0.0002153681,0.0001814818,0.0002930402,0.0002197779,0.001308639],"category_scores_gemma":[0.0001229238,0.0001572136,0.0001717776,0.0001486758,0.0001725739,0.0002044287,0.000159332,0.0002062586,0.0002965814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002983311,"about_ca_system_score_gemma":0.0002234551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001898,"about_ca_topic_score_gemma":0.003861611,"domain_scores_codex":[0.9999213,0.000004325358,0.000003228564,0.00001513064,0.00003822734,0.00001771669],"domain_scores_gemma":[0.9999508,0.000007577185,0.00001337785,0.000006361636,0.00001357495,0.00000836727],"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":[0.00004426666,0.000004515061,0.00005677218,0.00001447396,0.000001394657,0.00002091665,0.000009726174,0.0001509847,0.9989443,0.00007719256,0.00002619191,0.0006491992],"study_design_scores_gemma":[0.000005838039,0.00007847408,0.001411157,0.000002089796,0.000006706737,0.00003389017,0.00001621874,0.003760815,0.9938141,0.00001873353,0.0008465729,0.000005338155],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957405,0.0003723605,0.002102371,0.00004242609,0.00003045584,0.000004269769,0.00006359278,0.00005500296,0.001588905],"genre_scores_gemma":[0.9966576,0.0001269358,0.001512511,0.00001050869,0.000004406686,0.000002462738,0.00003939149,0.00001852659,0.001627681],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001898,"threshold_uncertainty_score":0.004377842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006613334250691058,"score_gpt":0.2061361280380959,"score_spread":0.1995227937874048,"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."}}