{"id":"W4311690273","doi":"10.32920/21740762.v1","title":"Biofunctionalized 3-D Carbon Nano-Network Platform for Enhanced Fibroblast Cell Adhesion","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Graphene and Nanomaterials Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biocompatibility; Nanotechnology; Nanotopography; Cell adhesion; Nanomaterials; Chemistry; Cell; Adhesion; Materials science; Biophysics; Biochemistry; Biology","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":[0.0001232994,0.0003172566,0.0003551597,0.0001026387,0.0001460503,0.00004898559,0.000259849,0.0002666152,0.00114219],"category_scores_gemma":[0.000003842894,0.0003271982,0.0002108735,0.0001629016,0.00001396785,0.00003078043,0.0002530744,0.0001912714,0.00001728589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001143414,"about_ca_system_score_gemma":0.00004328888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006544563,"about_ca_topic_score_gemma":0.00002549119,"domain_scores_codex":[0.9986917,0.00001151861,0.0004101025,0.0003907289,0.0001599878,0.0003359296],"domain_scores_gemma":[0.9992252,0.00009105723,0.00009264491,0.0004771746,0.00004426481,0.00006965731],"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":[0.0000951324,0.00005497933,0.00001475725,0.0009158482,0.0001191786,3.49578e-7,0.00007968775,0.1602567,0.8167943,0.001387002,0.01984708,0.0004349723],"study_design_scores_gemma":[0.001017378,0.000107172,0.0001907604,0.0001076461,0.0001105963,9.962578e-7,0.00005360106,0.01171656,0.879872,0.0142395,0.09162387,0.0009599529],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9154359,0.001015153,0.02460541,0.00004670666,0.004095682,0.003018985,0.0004910245,0.001883795,0.04940738],"genre_scores_gemma":[0.9804102,0.0003050375,0.01081192,0.00004335059,0.0006099527,0.004109736,0.001509208,0.0001328804,0.002067704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1485401,"threshold_uncertainty_score":0.999918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01323267942487475,"score_gpt":0.215431823848951,"score_spread":0.2021991444240763,"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."}}