{"id":"W3033134582","doi":"10.1039/d0sm00876a","title":"Enzymatically degradable, starch-based layer-by-layer films: application to cytocompatible single-cell nanoencapsulation","year":2020,"lang":"en","type":"article","venue":"Soft Matter","topic":"Polymer Surface Interaction Studies","field":"Materials Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Fundação para a Ciência e a Tecnologia; Ministério da Ciência, Tecnologia e Ensino Superior; H2020 European Research Council; National Research Foundation of Korea","keywords":"Layer by layer; Layer (electronics); Starch; Polymer; Degradation (telecommunications); Saccharomyces cerevisiae; Chemistry; S-layer; Chemical engineering; Amylase; Nanotechnology; Materials science; Enzyme; Biochemistry; Yeast; Organic chemistry; Computer science","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001506041,0.0002319859,0.000270451,0.00006418956,0.0001418539,0.0001515122,0.0002880976,0.00006238445,0.002750145],"category_scores_gemma":[0.00006167332,0.0002156977,0.00006186013,0.0002653772,0.00005759409,0.0002893714,0.0001083865,0.0001114556,0.01187358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006913496,"about_ca_system_score_gemma":0.00003943082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001116863,"about_ca_topic_score_gemma":0.00001331821,"domain_scores_codex":[0.9981623,0.00009047297,0.000438753,0.0005021581,0.0004242124,0.0003821095],"domain_scores_gemma":[0.9990022,0.0001862315,0.0001563637,0.0003286315,0.0001215877,0.0002049815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007753372,0.00009695388,0.00204165,0.00005772935,0.000005512238,8.862409e-7,0.000385654,0.0004943932,0.9177603,0.000007347519,0.0789172,0.0001548619],"study_design_scores_gemma":[0.0003187968,0.0001374327,0.000598614,0.00002478903,0.00001596325,7.782908e-7,0.0001011356,0.003449306,0.9797218,0.00004327113,0.01532852,0.0002596142],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7631208,0.00008120701,0.222071,0.01145218,0.0002144943,0.0007680816,0.0001003347,0.0002879345,0.001904019],"genre_scores_gemma":[0.9739538,3.950427e-7,0.01175829,0.01351167,0.00005950559,0.000202505,0.00002720509,0.00003947752,0.0004471058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2108331,"threshold_uncertainty_score":0.9981615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0313529421487418,"score_gpt":0.2641617697113663,"score_spread":0.2328088275626245,"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."}}