{"id":"W2129649722","doi":"10.4028/www.scientific.net/ssp.116-117.457","title":"Fluid Flow Investigation of Die Cast Tensile Test Bars","year":2006,"lang":"en","type":"article","venue":"Diffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi; National Research Council Canada","funders":"National Research Council Canada; Université du Québec à Chicoutimi","keywords":"Materials science; Die (integrated circuit); Die casting; Ultimate tensile strength; Tensile testing; Casting; Aluminium; Alloy; Flow (mathematics); Finite element method; Fluid dynamics; Composite material; Metallurgy; Structural engineering; Mechanics; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002482469,0.0002959774,0.0004174684,0.0005010183,0.0004023235,0.0004169036,0.0003192328,0.0005304741,0.001236913],"category_scores_gemma":[0.0005245478,0.0001449382,0.0001967141,0.000166828,0.000415107,0.000253075,0.0001671806,0.0003875908,0.0002180757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004266542,"about_ca_system_score_gemma":0.000304622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001519593,"about_ca_topic_score_gemma":0.001229753,"domain_scores_codex":[0.9998281,0.00001795484,0.000007186091,0.00003353434,0.00008230378,0.000030902],"domain_scores_gemma":[0.9997038,0.0001040724,0.00004211983,0.00002009458,0.00009975265,0.00003015777],"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":[0.0001378083,0.00005450805,0.0009157675,0.00004337931,0.000004609508,0.000130787,0.00007216435,0.002906284,0.991196,0.0004541301,0.0000521956,0.004032389],"study_design_scores_gemma":[0.00002433443,0.0004599179,0.005363002,0.00001302724,0.000007795266,0.00008221693,0.00007586794,0.03114117,0.9614088,0.0001068873,0.001297111,0.0000198881],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991887,0.0002036239,0.006427142,0.00002451576,0.00002211401,0.00002454678,0.0001117751,0.0001128491,0.00118641],"genre_scores_gemma":[0.9947051,0.0000885347,0.003793303,0.00001036707,0.000004713084,0.00001416084,0.0001230841,0.00001278327,0.001247931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001519593,"threshold_uncertainty_score":0.004137874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0223111602400695,"score_gpt":0.2380687713215021,"score_spread":0.2157576110814326,"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."}}