{"id":"W1972950419","doi":"10.4028/www.scientific.net/msf.519-521.1461","title":"Understanding T-Ingot Horizontal DC Casting Using Process Modelling","year":2006,"lang":"en","type":"article","venue":"Materials science forum","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ingot; Process (computing); Casting; Foundry; Materials science; Mechanical engineering; Production (economics); Work (physics); Aluminium; Metallurgy; Manufacturing engineering; Process engineering; Computer science; Engineering","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":[0.0003453213,0.0002087083,0.0001964626,0.0001674881,0.0005353582,0.000484453,0.0003265851,0.00006013272,0.00003430973],"category_scores_gemma":[0.00001580733,0.000193634,0.00002387549,0.0003649812,0.0002867266,0.000811561,0.00006685738,0.00007448097,0.00001032352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000501706,"about_ca_system_score_gemma":0.00008636607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001982724,"about_ca_topic_score_gemma":0.00003241291,"domain_scores_codex":[0.9982951,0.000009566528,0.0003095415,0.0002986568,0.0003268864,0.0007602673],"domain_scores_gemma":[0.9996591,0.00001187167,0.00005909882,0.0001621616,0.00004892044,0.00005889387],"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":[0.000003160195,0.000001971553,0.0001179106,0.00004435496,0.000001711525,0.000002923812,0.0001990853,0.2903483,0.708772,0.0004921392,0.000008113762,0.000008292081],"study_design_scores_gemma":[0.00008947564,0.00001128477,0.000009674119,0.00007178726,0.000006452612,0.00005462837,0.0007883291,0.2079374,0.7892276,0.001543732,0.00001320504,0.0002464204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8887717,0.00006287703,0.1087802,0.00001240438,0.001039161,0.0001398126,0.00001153174,0.0002985652,0.0008837858],"genre_scores_gemma":[0.9953988,0.000001209088,0.004344572,0.000008713334,0.0001805999,0.00000527889,0.000002899029,0.00004616571,0.00001179313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1066271,"threshold_uncertainty_score":0.7896164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05791620608604356,"score_gpt":0.2326865424846133,"score_spread":0.1747703363985697,"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."}}