{"id":"W3165341099","doi":"10.3390/polym13101650","title":"Numerical Methods in Studies of Liquid Crystal Elastomers","year":2021,"lang":"en","type":"review","venue":"Polymers","topic":"Advanced Materials and Mechanics","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Finite element method; Computer science; Liquid crystal; Variety (cybernetics); Monte Carlo method; Categorization; Field (mathematics); Elastomer; Strengths and weaknesses; Mechanical engineering; Materials science; Biochemical engineering; Nanotechnology; Artificial intelligence; Physics; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001790546,0.000291223,0.001862476,0.0001515116,0.00001074348,0.000004532673,0.000123856,0.0001593378,0.00008166755],"category_scores_gemma":[0.00007703681,0.0002624117,0.0002496894,0.0003332153,0.00002849813,0.0000380985,0.0000586235,0.0001786598,0.000004147809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001071392,"about_ca_system_score_gemma":0.00005721836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004524997,"about_ca_topic_score_gemma":9.252782e-7,"domain_scores_codex":[0.9987707,0.0001203564,0.000559381,0.0001962743,0.00009241547,0.0002608432],"domain_scores_gemma":[0.9994542,0.0001703602,0.000103938,0.0002014062,0.00001671698,0.00005337281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003021519,0.00001175672,1.098291e-8,0.01539131,0.000274418,0.00001652624,0.0001300183,0.0002624052,0.0007120713,0.0001905521,0.00003856411,0.9829693],"study_design_scores_gemma":[0.00008356782,0.00004331207,1.174418e-8,0.0056184,0.000214423,0.00001446323,0.00019439,0.00002564578,0.002738707,0.00001172541,0.9907308,0.0003246121],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00000420261,0.9923116,0.005904006,0.000001561826,0.001233635,0.0001386644,0.00002175281,0.00005761489,0.0003269597],"genre_scores_gemma":[0.000007727298,0.9867815,0.01295015,0.00000456892,0.00006247744,0.00005153644,0.00001477997,0.00007360681,0.0000536488],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9906922,"threshold_uncertainty_score":0.9999828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07180473470836947,"score_gpt":0.4192855818956547,"score_spread":0.3474808471872852,"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."}}