{"id":"W4396733140","doi":"10.1016/j.compstruct.2024.118179","title":"Design and optimization of Anisotropy–Inspired AlSi10Mg metamaterials with tailored mechanics and mass transport properties in tissue engineering","year":2024,"lang":"en","type":"article","venue":"Composite Structures","topic":"Cellular and Composite Structures","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"National Key Research and Development Program of China; National Key Laboratory Foundation of China","keywords":"Anisotropy; Materials science; Metamaterial; Tissue engineering; Topology optimization; Mechanical engineering; Composite material; Material Design; Mechanics; Structural engineering; Finite element method; Engineering; Physics; Biomedical engineering; Optoelectronics","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":[0.00005882104,0.0002415159,0.000318196,0.0001813771,0.00002953834,0.00007837157,0.00008554936,0.00006201922,0.00001866966],"category_scores_gemma":[0.00000171082,0.0001930462,0.00001987102,0.0001509231,0.00002828676,0.0001399472,0.00001579066,0.00009913534,1.733894e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001937391,"about_ca_system_score_gemma":0.00001058461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001341952,"about_ca_topic_score_gemma":0.0000022261,"domain_scores_codex":[0.9992044,0.00002473133,0.0002504935,0.0002210785,0.0001236149,0.0001756983],"domain_scores_gemma":[0.9997613,0.0000213045,0.00002123901,0.0001244775,0.00002075635,0.00005087763],"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":[0.00003523658,0.000001303717,0.00001684861,0.0003344777,0.00004895147,0.00002814352,0.0002521308,0.5320197,0.4666008,0.0003750316,0.000001057666,0.0002862912],"study_design_scores_gemma":[0.0002341356,0.00006912788,0.000230107,0.0001304455,0.00006489393,0.00008441052,0.00001569836,0.6115586,0.3869475,0.0004112629,0.00005366477,0.0002000975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4806759,0.006941441,0.5116977,0.000008428315,0.0001571741,0.0003132981,0.00001028304,0.0001790602,0.00001672959],"genre_scores_gemma":[0.9267955,0.0002608532,0.0728301,0.000003502491,0.00002546074,0.00001179239,0.00001845135,0.00004956399,0.000004715046],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4461197,"threshold_uncertainty_score":0.7872194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007238138571171796,"score_gpt":0.1802317482345694,"score_spread":0.1729936096633976,"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."}}