{"id":"W2335017003","doi":"10.1021/acs.biomac.5b00219","title":"Development of a Polyester Coating Combining Antithrombogenic and Cell Adhesive Properties: Influence of Sequence and Surface Density of Adhesion Peptides","year":2015,"lang":"en","type":"article","venue":"Biomacromolecules","topic":"Nanofabrication and Lithography Techniques","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Polytechnique Montréal","funders":"Institut de Cardiologie de Montréal; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Polyester; Adhesive; Adhesion; Coating; Sequence (biology); Cell adhesion; Materials science; Polymer chemistry; Polymer science; Chemistry; Chemical engineering; Nanotechnology; Composite material; Biochemistry; Layer (electronics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001609428,0.0001060256,0.0002052453,0.00007810086,0.00002279194,0.000007539869,0.0000745633,0.00004829348,3.920558e-7],"category_scores_gemma":[0.00002482803,0.00009675669,0.00002038681,0.0001614112,0.0001559534,0.00008356755,0.00005619581,0.00003178214,2.224711e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001131959,"about_ca_system_score_gemma":0.0000419777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005863088,"about_ca_topic_score_gemma":0.000006853231,"domain_scores_codex":[0.999321,0.0000250685,0.0003104314,0.0001184519,0.0001270492,0.00009796587],"domain_scores_gemma":[0.9995442,0.00002230533,0.0001264198,0.0001119814,0.0001415382,0.0000535527],"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":[0.000008264816,0.00001761396,0.02366066,0.0003307637,0.00001448324,9.057148e-7,0.002954525,0.0000197662,0.9725977,0.00003444352,0.000003832169,0.0003570411],"study_design_scores_gemma":[0.000169683,0.00006001021,0.02235315,0.00025468,0.00001058991,0.000006021281,0.0005220046,0.0002455311,0.976243,0.00001738264,0.0000135115,0.000104414],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983059,0.0009315658,0.0005000494,0.000002903457,0.000008225597,0.0001337268,0.000005760954,0.00005231698,0.00005958463],"genre_scores_gemma":[0.9576582,0.00006315983,0.04225709,0.000003919324,0.000001092989,0.000002761654,0.000001583955,0.000010418,0.000001822965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04175704,"threshold_uncertainty_score":0.3945623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03066840837393358,"score_gpt":0.236951528579054,"score_spread":0.2062831202051204,"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."}}