{"id":"W2528664998","doi":"10.1021/acsbiomaterials.6b00374","title":"Metal Chelation Dynamically Regulates the Mechanical Properties of Engineered Protein Hydrogels","year":2016,"lang":"en","type":"article","venue":"ACS Biomaterials Science & Engineering","topic":"Cellular Mechanics and Interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Self-healing hydrogels; Chelation; Biophysics; Protein engineering; Metal ions in aqueous solution; Materials science; Protein folding; Folding (DSP implementation); Conformational change; Chemistry; Metal; Nanotechnology; Polymer chemistry; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001574393,0.0003136532,0.0001230908,0.0001124084,0.00008762249,0.0002426029,0.0002004644,0.0001976835,0.0004581404],"category_scores_gemma":[0.0001764205,0.0001615011,0.0001214712,0.00008321656,0.0001876702,0.0002738418,0.0001663578,0.0002929851,0.0001212531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000208547,"about_ca_system_score_gemma":0.00008617123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001660628,"about_ca_topic_score_gemma":0.0003723982,"domain_scores_codex":[0.9998964,0.00001049862,0.00001036315,0.00003103326,0.0000288125,0.00002280017],"domain_scores_gemma":[0.9998641,0.00003040973,0.00005631163,0.00001082342,0.0000174782,0.00002091707],"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":[0.00001244096,0.000005444394,0.00003896275,0.00001084939,0.000001385209,0.000008761206,0.000006363824,0.00005799339,0.9994461,0.00003091831,0.000009885347,0.0003708883],"study_design_scores_gemma":[0.00000316711,0.0000315127,0.00041236,0.000001184052,0.00000246754,0.00001782821,0.000004131324,0.001078453,0.9981345,0.00001233835,0.0002988471,0.000003070611],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922995,0.0005353906,0.005958224,0.00006670113,0.00002451697,0.00001918395,0.0001014847,0.0001010234,0.0008940408],"genre_scores_gemma":[0.9954284,0.0002902814,0.003486853,0.0000468109,0.000006433925,0.00002351406,0.0000538234,0.00002239319,0.0006413978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004581404,"threshold_uncertainty_score":0.001532674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008138384756558942,"score_gpt":0.1991717190442996,"score_spread":0.1910333342877407,"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."}}