{"id":"W4313646565","doi":"10.1017/s0890060422000233","title":"Neural networks with dimensionality reduction for predicting temperature change due to plastic deformation in a cold rolling simulation","year":2023,"lang":"en","type":"article","venue":"Artificial intelligence for engineering design analysis and manufacturing","topic":"Metallurgy and Material Forming","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dimensionality reduction; Artificial neural network; Nonlinear system; Curse of dimensionality; Reduction (mathematics); Dimension (graph theory); Computation; Process (computing); Principal component analysis; Deformation (meteorology); Computer science; Algorithm; Control theory (sociology); Materials science; Mathematics; Artificial intelligence; Physics; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004893987,0.0001818074,0.0002666271,0.0005190431,0.0001350875,0.0000933201,0.00005461019,0.00008833517,0.000002277764],"category_scores_gemma":[0.00006004224,0.0001711761,0.00006817424,0.0005492399,0.000007014281,0.0003021522,0.00001475044,0.00009454296,0.000001055161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005051114,"about_ca_system_score_gemma":0.000003179252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002237584,"about_ca_topic_score_gemma":0.00004132204,"domain_scores_codex":[0.9989765,0.00001229959,0.000360805,0.0002274871,0.0001002539,0.0003226191],"domain_scores_gemma":[0.9994639,0.000292024,0.00004134078,0.00009407375,0.00003502744,0.00007365588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008377561,0.000004510893,0.00001245891,0.00009694214,0.00009295522,0.000001441603,0.0003249074,0.9862445,0.008612718,0.000146994,7.668215e-7,0.004378032],"study_design_scores_gemma":[0.00004170052,0.00005631683,0.0003253553,0.00005400744,0.000120613,0.000001486854,0.00009506938,0.9128823,0.08613884,0.00008730028,0.00001585869,0.0001811671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4650882,0.00001369836,0.5341434,0.000008766893,0.0002027003,0.0004038,0.000004067841,0.0001351081,2.221468e-7],"genre_scores_gemma":[0.9950003,0.000008772726,0.004386939,0.000005033257,0.00019984,0.0003089125,0.00005755236,0.00002997931,0.000002665553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5299121,"threshold_uncertainty_score":0.6980359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03905312288646864,"score_gpt":0.2511042695288267,"score_spread":0.2120511466423581,"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."}}