{"id":"W2778688546","doi":"10.1021/acsami.7b15756","title":"Universal Mussel-Inspired Ultrastable Surface-Anchoring Strategy via Adaptive Synergy of Catechol and Cations","year":2017,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Polymer Surface Interaction Studies","field":"Materials Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; China Scholarship Council; Canada Foundation for Innovation; Alberta Innovates - Technology Futures","keywords":"Catechol; Anchoring; Materials science; Ligand (biochemistry); Amine gas treating; Force spectroscopy; Moiety; Coating; Surface engineering; Cationic polymerization; Nanotechnology; Biofouling; Chemical engineering; Combinatorial chemistry; Organic chemistry; Polymer chemistry; Chemistry; Membrane; Atomic force microscopy","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":[0.00008042713,0.0004079696,0.0001910981,0.0001059219,0.0001149667,0.0002079559,0.000314842,0.0004038958,0.0003467817],"category_scores_gemma":[0.0001173459,0.0001471409,0.0001912144,0.00009063388,0.0001842541,0.0003137041,0.0003759886,0.0003249866,0.000181106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001839774,"about_ca_system_score_gemma":0.0001201674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000356369,"about_ca_topic_score_gemma":0.0009441565,"domain_scores_codex":[0.9999336,0.000007336822,0.000005185818,0.00002186705,0.00001619033,0.00001573733],"domain_scores_gemma":[0.9999185,0.00001118605,0.00002826961,0.000008365867,0.00001337349,0.00002032798],"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":[0.00000915017,0.000005835025,0.00005409617,0.00003522691,0.000003614066,0.00003211621,0.000009760661,0.00005859654,0.9983972,0.00007577214,0.00001783519,0.001300831],"study_design_scores_gemma":[0.000004754063,0.00006269659,0.0004360171,0.000002255837,0.00001005194,0.0001029274,0.000008601281,0.0011965,0.9965468,0.00002344016,0.001598048,0.000007781416],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9744394,0.001466095,0.02157982,0.0001507043,0.00004683533,0.00003196122,0.00007400273,0.0001549742,0.002056236],"genre_scores_gemma":[0.9850194,0.0006703524,0.01230007,0.0000758867,0.000009850009,0.00002063976,0.00007285956,0.00001821111,0.001812644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004079696,"threshold_uncertainty_score":0.001334906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0255314370151916,"score_gpt":0.2675150537291138,"score_spread":0.2419836167139222,"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."}}