{"id":"W1579657918","doi":"10.1007/978-3-319-48150-0_52","title":"Texture Development in an Extruded Magnesium Alloy During Compression Along the Transverse Direction","year":2013,"lang":"en","type":"book-chapter","venue":"","topic":"Magnesium Alloys: Properties and Applications","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Materials science; Extrusion; Anisotropy; Work hardening; Texture (cosmology); Magnesium alloy; Magnesium; Transverse plane; Alloy; Metallurgy; Compression (physics); Hardening (computing); Strain hardening exponent; Composite material; Compressive strength; Microstructure; Optics; Structural engineering; Physics; Artificial intelligence","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":[0.00005789058,0.0001322733,0.000164188,0.0001456726,0.0002343478,0.0002991385,0.0002160874,0.000176778,0.001691742],"category_scores_gemma":[0.0001704507,0.0001553502,0.0001344237,0.0002943147,0.0003188088,0.0001934997,0.0001233726,0.0002255359,0.0002118676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002871918,"about_ca_system_score_gemma":0.0002072272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001820736,"about_ca_topic_score_gemma":0.003091411,"domain_scores_codex":[0.9999465,0.000002554397,0.000001528534,0.00001219433,0.00002456681,0.00001272319],"domain_scores_gemma":[0.999947,0.00001374941,0.00001296898,0.000006057419,0.00001330626,0.000006893883],"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":[0.0004056537,0.00002994248,0.0009296693,0.0000607115,0.00000461687,0.0004693558,0.0001465748,0.0006220632,0.986169,0.0006312759,0.0002200674,0.01031105],"study_design_scores_gemma":[0.00003155735,0.000438086,0.02634153,0.00001329488,0.00001710731,0.0006815657,0.0001972901,0.005672513,0.9601995,0.000271684,0.006117539,0.00001839273],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867412,0.001142296,0.001969374,0.0000659314,0.000045539,0.00001563316,0.0001438581,0.00005227389,0.009823909],"genre_scores_gemma":[0.9911947,0.0002995476,0.00107096,0.00002033298,0.00001016823,0.000005335869,0.0001058572,0.00002121453,0.007271769],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001820736,"threshold_uncertainty_score":0.005659401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0207923660805209,"score_gpt":0.2180939297027642,"score_spread":0.1973015636222433,"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."}}