{"id":"W4414684052","doi":"10.1038/s44334-025-00055-8","title":"Computationally tuned dual-layer lattice pads adapted to gait-induced pressure distribution","year":2025,"lang":"en","type":"article","venue":"npj Advanced Manufacturing","topic":"Advanced Materials and Mechanics","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Science Foundation of Ningbo; K. C. Wong Magna Fund in Ningbo University; National Key Research and Development Program of China; China Scholarship Council; Széchenyi István Egyetem; Ningbo University","keywords":"Bayesian optimization; Scalability; Finite element method; Parametric statistics; Forefoot; Lattice (music); Genetic algorithm; Engineering design process; Gaussian process","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009162714,0.0002896648,0.0002985318,0.00009265943,0.0001359529,0.00006477093,0.0001506898,0.000120239,0.00004977336],"category_scores_gemma":[0.00005232087,0.0003132462,0.00005831178,0.0001562604,0.000007641367,0.0002745964,0.00009605043,0.0001893475,0.00004375832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001307273,"about_ca_system_score_gemma":0.00002303048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005304989,"about_ca_topic_score_gemma":0.00000857681,"domain_scores_codex":[0.9986592,0.00001998661,0.0003408461,0.0003479486,0.0001979747,0.0004340317],"domain_scores_gemma":[0.9993808,0.00007858509,0.00005022053,0.0002930342,0.00007268033,0.0001247152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007160803,0.00002377133,0.000001679202,0.0002080887,0.00007258332,0.00001000799,0.00007249963,0.5665631,0.4058726,0.003728849,0.0003267315,0.02304849],"study_design_scores_gemma":[0.0007717204,0.00003874907,0.001438043,0.0001726853,0.00005163535,0.000003562648,0.00004996358,0.009550109,0.9162584,0.003524605,0.06774195,0.0003985947],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.579492,0.0001860009,0.415866,0.0001688044,0.001432677,0.0005472912,0.0001138368,0.0008509365,0.001342482],"genre_scores_gemma":[0.9866357,0.00003222307,0.01231901,0.000209436,0.0001010537,0.00007977157,0.0001395492,0.00004715625,0.0004361116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.557013,"threshold_uncertainty_score":0.999932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009866938259309897,"score_gpt":0.2434520093553905,"score_spread":0.2335850710960806,"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."}}