{"id":"W3100237484","doi":"10.3139/146.111960","title":"Investigation of the effect of solidification rate on microstructure of Al-0.13Si-0.3Fe DC-cast alloy using EBSD and DSC techniques","year":2020,"lang":"en","type":"article","venue":"International Journal of Materials Research (formerly Zeitschrift fuer Metallkunde)","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi; Université du Québec en Abitibi-Témiscamingue; Saint Mary's University","funders":"","keywords":"Intermetallic; Materials science; Microstructure; Ingot; Alloy; Metallurgy; Scanning electron microscope; Differential scanning calorimetry; Electron backscatter diffraction; Mischmetal; Casting; Composite material; Thermodynamics","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":[0.0001830525,0.0001715272,0.0001987083,0.0002633618,0.0001236411,0.0002134701,0.0001745926,0.0001497731,0.0009403945],"category_scores_gemma":[0.0003550551,0.0001610966,0.0001373353,0.0002363789,0.0001308196,0.0001488724,0.00006478029,0.0002554831,0.0001871919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002278835,"about_ca_system_score_gemma":0.0001349073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001481032,"about_ca_topic_score_gemma":0.004259897,"domain_scores_codex":[0.9998577,0.0000135698,0.00001117527,0.00003273774,0.00006973144,0.00001504784],"domain_scores_gemma":[0.9997476,0.00007385494,0.0000544951,0.00002120654,0.00008844551,0.00001443993],"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":[0.00005886963,0.00001064658,0.0006945915,0.00003583197,0.000004021099,0.00003053557,0.00003486823,0.0003133467,0.9968461,0.00002988602,0.00001555386,0.00192581],"study_design_scores_gemma":[0.000001891384,0.00006757766,0.008942717,0.000002219329,0.000007149167,0.00003086107,0.00002019645,0.001957483,0.9886116,0.000008494364,0.0003454528,0.0000042475],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970144,0.0005785189,0.00134816,0.00001190475,0.00001047469,0.000009450165,0.0001472875,0.00003947382,0.0008404586],"genre_scores_gemma":[0.9973381,0.000216919,0.001553842,0.000006017477,0.000002364471,0.000007110065,0.00008635876,0.00001881765,0.0007703917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001481032,"threshold_uncertainty_score":0.003145874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04291697484840825,"score_gpt":0.3068385068249154,"score_spread":0.2639215319765072,"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."}}