{"id":"W6920582771","doi":"10.60692/dvwcs-nc131","title":"Optimization of Neural Network architecture and derivation of closed-form equation to predict ultimate load of functionally graded material plate","year":2023,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Composite Structure Analysis and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Parametric statistics; Artificial neural network; Set (abstract data type); Power (physics); Backpropagation; Obstacle; Parametric model; Variance (accounting)","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":[0.0002091464,0.0001368387,0.0002686008,0.0003421388,0.00004300049,0.00003305128,0.00006927826,0.00008511887,0.00001260675],"category_scores_gemma":[0.00001314097,0.0001235321,0.00005304108,0.0006286863,0.00001541433,0.0003317177,0.00003025994,0.00004059559,0.000003256645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004987419,"about_ca_system_score_gemma":0.00001309172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007270167,"about_ca_topic_score_gemma":6.421918e-7,"domain_scores_codex":[0.9986784,0.00002435029,0.0007760727,0.00008594619,0.0003043404,0.0001308724],"domain_scores_gemma":[0.9992344,0.00001054206,0.0003136153,0.0001523405,0.0002499962,0.00003913548],"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":[0.00009785951,5.425242e-7,0.005609177,0.000516733,0.00005530192,8.727302e-8,0.007618169,0.9852602,0.0002400784,0.00005372782,0.00002273063,0.0005253349],"study_design_scores_gemma":[0.0004366922,0.00005300565,0.04617944,0.0001218012,0.00005301392,0.000003426211,0.0003569209,0.9495246,0.003155343,0.00000645007,0.00000554657,0.0001037046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.680873,0.000001855909,0.3182795,0.000007443438,0.0002388729,0.0002612046,0.00009487085,0.000120585,0.000122633],"genre_scores_gemma":[0.9957739,9.993111e-7,0.003784208,0.000006734402,0.00006074116,0.00001487692,0.0003421621,0.00001197404,0.000004367891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3149009,"threshold_uncertainty_score":0.5037492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01214364125833467,"score_gpt":0.1760593104093999,"score_spread":0.1639156691510652,"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."}}