{"id":"W2322498787","doi":"10.1007/s40962-016-0038-2","title":"Optimizing the Heat Treatment of High-Strength 7075-Type Wrought Alloys: A Metallographic Study","year":2016,"lang":"en","type":"article","venue":"International Journal of Metalcasting","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Materials science; Ultimate tensile strength; Alloy; Precipitation hardening; Metallurgy; Precipitation; Homogenization (climate); Hardening (computing); Structural material; Tensile testing; Energy-dispersive X-ray spectroscopy; Composite material; Scanning electron microscope","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":[0.000353397,0.0002147803,0.0003718184,0.0002517533,0.00004674926,0.00005223911,0.0005103876,0.00004032056,0.00007580033],"category_scores_gemma":[0.0001559234,0.0001037987,0.0002180383,0.00016462,0.00008481995,0.0003048499,0.00005861248,0.0001130185,0.000003912322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001628728,"about_ca_system_score_gemma":0.00003636886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004487273,"about_ca_topic_score_gemma":0.00002489043,"domain_scores_codex":[0.9983665,0.00008560833,0.000714623,0.0001229646,0.0005249326,0.0001854151],"domain_scores_gemma":[0.9988033,0.0002732676,0.000236621,0.0001716471,0.0004632104,0.000051958],"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":[0.0004966995,0.0006110703,0.01108512,0.00002832746,0.01220518,0.0003574366,0.007408772,0.03702324,0.8402285,0.0002865503,0.0001179332,0.0901512],"study_design_scores_gemma":[0.02451664,0.009246721,0.03676553,0.001961741,0.004138411,0.005987655,0.0111161,0.01098953,0.8666027,0.001620705,0.02478874,0.002265535],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936519,0.002380737,0.001613241,0.0002224595,0.001834482,0.0001368772,0.000008228169,0.00003166583,0.0001204682],"genre_scores_gemma":[0.9949778,0.0003532369,0.004157739,0.00001186798,0.0003936836,0.000004123727,9.312126e-7,0.00003382254,0.00006674977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08788566,"threshold_uncertainty_score":0.4232787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02161299680143332,"score_gpt":0.2459281880441793,"score_spread":0.224315191242746,"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."}}