{"id":"W3032056106","doi":"10.1007/s11661-020-05826-w","title":"High Electrical and Thermal Conductivity Cast Al-Fe-Mg-Si Alloys with Ni Additions","year":2020,"lang":"en","type":"article","venue":"Metallurgical and Materials Transactions A","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; University of Guelph","funders":"","keywords":"Materials science; Intermetallic; Alloy; Electrical resistivity and conductivity; Microstructure; Metallurgy; Castability; Aluminium; Indentation hardness; Thermal conductivity; Casting; Composite material","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005208209,0.0002095912,0.000334327,0.00002906082,0.0001481374,0.0001354208,0.00005746558,0.00008806168,0.001569345],"category_scores_gemma":[0.00000434404,0.0001614225,0.00003205278,0.00011005,0.0001755251,0.0002266435,0.000008599608,0.000166064,0.00001525246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001353201,"about_ca_system_score_gemma":0.00001228659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001237434,"about_ca_topic_score_gemma":0.00004159451,"domain_scores_codex":[0.9991565,0.00004801106,0.0001958852,0.0002585114,0.0001053404,0.0002356887],"domain_scores_gemma":[0.9996758,0.00002600721,0.0000205377,0.0000852194,0.00002381912,0.0001686043],"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":[0.0001269083,0.00003302418,0.000001615568,0.00006846841,0.0002058196,0.00003972094,0.000260239,0.001029326,0.9965949,0.0002184654,0.0001195464,0.001301948],"study_design_scores_gemma":[0.008577887,0.001974581,0.01104603,0.0001524777,0.001882506,0.004024161,0.0005047759,0.02512911,0.82661,0.000435065,0.1159177,0.003745682],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.966544,0.0002451326,0.03173531,0.0006489283,0.0001307276,0.0002004966,0.0001819601,0.0002495532,0.00006392336],"genre_scores_gemma":[0.9972809,0.0001619305,0.002116184,0.0001820866,0.00007580388,0.00005315066,0.00002360157,0.00003612125,0.00007020811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1699849,"threshold_uncertainty_score":0.9993433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012087012671035,"score_gpt":0.1737598237631069,"score_spread":0.1636389536363965,"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."}}