{"id":"W2163869340","doi":"10.1016/j.biomaterials.2012.05.001","title":"High-throughput cellular screening of engineered ECM based on combinatorial polyelectrolyte multilayer films","year":2012,"lang":"en","type":"article","venue":"Biomaterials","topic":"Polymer Surface Interaction Studies","field":"Materials Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Materials science; Polyelectrolyte; Viability assay; Tissue engineering; Biocompatibility; Extracellular matrix; Nanotechnology; Coating; HEK 293 cells; Polymer; Cell culture; Biomedical engineering; Cell; Composite material; Cell biology; Chemistry; Biology; 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007106143,0.0003190025,0.0005904824,0.0001559914,0.000139405,0.00007152354,0.0002842021,0.0001403633,0.001755476],"category_scores_gemma":[0.0001679958,0.0002800901,0.0001162156,0.0001637975,0.0001035676,0.0003358866,0.0001060533,0.00002467246,0.0003929686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004617564,"about_ca_system_score_gemma":0.00003173756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003543909,"about_ca_topic_score_gemma":9.306916e-7,"domain_scores_codex":[0.9976933,0.0002245583,0.0006335633,0.000327161,0.0004658006,0.0006556145],"domain_scores_gemma":[0.9987359,0.0002035061,0.0003469401,0.0004858731,0.00009189115,0.0001358876],"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":[0.0003662818,0.0001873291,0.0001644997,0.00003272972,0.00003347117,0.000002448514,0.0001780351,0.0001054105,0.9975991,0.0002918138,0.0009877407,0.00005120108],"study_design_scores_gemma":[0.001122068,0.000158174,0.0008004279,0.0000591374,0.00003608207,0.000001958503,0.00004892239,0.0001952249,0.9962209,0.00001473158,0.001062064,0.0002802734],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98642,0.000223804,0.001518087,0.000110612,0.01088569,0.0002640995,0.0002124858,0.0002109317,0.0001542653],"genre_scores_gemma":[0.9939238,0.000002911207,0.005219119,0.00008075723,0.0005953913,0.00004252319,0.00002524402,0.00004659301,0.00006360696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0102903,"threshold_uncertainty_score":0.9999651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02042471546319284,"score_gpt":0.2611524724952092,"score_spread":0.2407277570320164,"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."}}