{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004867028,0.0003205265,0.00007995607,0.0002568399,0.0001314851,0.0001739315,0.0001973223,0.0004907481,0.001003637],"category_scores_gemma":[0.00007847694,0.0001021786,0.0001224473,0.0001484365,0.0001060415,0.0001797764,0.0001271998,0.0002088363,0.0002540428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002541624,"about_ca_system_score_gemma":0.0001257855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006221498,"about_ca_topic_score_gemma":0.002133714,"domain_scores_codex":[0.9999495,0.000004190415,0.000002355561,0.00001277033,0.00002185777,0.000009417222],"domain_scores_gemma":[0.9999629,0.000007146407,0.0000101355,0.000004179879,0.000007013559,0.000008592242],"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":[0.000008182144,0.00000862387,0.00002139795,0.00002240508,0.000001626491,0.00003808617,0.000003919752,0.0002791842,0.9983095,0.00009671803,0.0000390797,0.001171169],"study_design_scores_gemma":[0.00000690147,0.00007064754,0.0008866073,0.000003369692,0.00000439344,0.0000819439,0.000007294983,0.003088518,0.9935642,0.00007070429,0.0022072,0.000008358286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797748,0.001642894,0.01134724,0.000133524,0.0001035822,0.00005837861,0.0004350206,0.0002580801,0.006246316],"genre_scores_gemma":[0.9834365,0.000545515,0.01310093,0.00005219714,0.000008921849,0.00004640934,0.0002405717,0.00002588677,0.002543061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001003637,"threshold_uncertainty_score":0.00335747,"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."}}