{"id":"W2165512725","doi":"10.1002/jbm.a.32357","title":"Bioactivating electrically conducting polypyrrole with fibronectin and bovine serum albumin","year":2009,"lang":"en","type":"article","venue":"Journal of Biomedical Materials Research Part A","topic":"Conducting polymers and applications","field":"Materials Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Hôpital Saint-François d'Assise","funders":"Canadian Institutes of Health Research","keywords":"Polypyrrole; Materials science; Bovine serum albumin; Membrane; Adhesion; Fibronectin; Conductive polymer; Tissue engineering; Polymerization; Polymer chemistry; Cell adhesion; Chemical engineering; Surface modification; Biomolecule; Interfacial polymerization; Polymer; Nanotechnology; Biomedical engineering; Extracellular matrix; Composite material; Monomer; Chemistry; Chromatography; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003548747,0.0001469578,0.0003882129,0.000295547,0.0003463481,0.0002788613,0.000306248,0.00009900568,0.0007073204],"category_scores_gemma":[0.0008574328,0.00009875829,0.00003385623,0.000563867,0.0003837635,0.0002705278,0.00008726594,0.0003637199,0.00001969113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005637166,"about_ca_system_score_gemma":0.000266001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006001794,"about_ca_topic_score_gemma":0.000002963197,"domain_scores_codex":[0.9971875,0.0003330814,0.000664524,0.0002682179,0.000939911,0.0006067862],"domain_scores_gemma":[0.9983358,0.0004066637,0.0003701936,0.0001949033,0.0003095834,0.0003828697],"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":[0.0002115137,0.000126883,0.00003638717,0.00002113694,0.00001164543,0.00003136665,0.0001458004,1.836873e-7,0.990516,0.00008328735,0.001599883,0.007215904],"study_design_scores_gemma":[0.000627343,0.001959885,0.0005329238,0.0001851321,0.00001228162,0.0003917239,0.0003627908,0.000005478292,0.9903976,0.0003558952,0.005039616,0.0001293738],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901907,0.0002127212,0.0001484093,0.008972775,0.0001633821,0.0001678063,0.00001677495,0.00002429418,0.0001031597],"genre_scores_gemma":[0.9960167,0.00004025522,0.002851548,0.0001241317,0.0007936956,0.000006270072,0.000002481635,0.00001475039,0.0001501534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008848644,"threshold_uncertainty_score":0.7744662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07548413988409697,"score_gpt":0.3658507073728228,"score_spread":0.2903665674887259,"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."}}