{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003793651,0.000343462,0.0006034749,0.00008074131,0.0006178306,0.0004386286,0.0006392081,0.000123819,0.000409198],"category_scores_gemma":[0.00006246593,0.0003236287,0.00001906844,0.00005990601,0.0005315074,0.0007675876,0.0004438179,0.0001071281,0.0001193639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007414756,"about_ca_system_score_gemma":0.00006010004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00450112,"about_ca_topic_score_gemma":0.0003201366,"domain_scores_codex":[0.9981042,0.00005328739,0.000573535,0.0005659459,0.0002599356,0.0004431448],"domain_scores_gemma":[0.9981174,0.0001659182,0.0007649509,0.0007054415,0.0001633784,0.00008285942],"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":[0.0001947317,0.0000540147,0.00007329859,0.00004325079,0.00007776656,0.000002972845,0.000802499,0.0002407122,0.9965891,0.001259719,0.0001544725,0.0005074162],"study_design_scores_gemma":[0.0004226003,0.00009332552,0.0009496781,0.00007091163,0.00005959865,0.0000065404,0.001813114,0.000004668747,0.9958172,0.0003438229,0.0001132409,0.0003052916],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944373,0.0002285492,0.0002285987,0.0001173727,0.0009020607,0.0003183368,0.0002407017,0.0001241208,0.003402953],"genre_scores_gemma":[0.9986556,0.000126322,0.0006353575,0.00001849961,0.00007604717,0.00003946726,0.000006783568,0.00003897171,0.0004029846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00421826,"threshold_uncertainty_score":0.9999216,"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."}}