{"id":"W2595973690","doi":"10.1038/srep44250","title":"Biofunctionalized 3-D Carbon Nano-Network Platform for Enhanced Fibroblast Cell Adhesion","year":2017,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Graphene and Nanomaterials Applications","field":"Engineering","cited_by":16,"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":"Fibroblast; Adhesion; Cell adhesion; Nano-; Cell; Chemistry; Cell biology; Computational biology; Biology; Materials science; Biochemistry; Composite material","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":[0.0003856132,0.0001289368,0.0001554956,0.00005961669,0.0007943686,0.0003495744,0.000157426,0.00008067491,0.00005560863],"category_scores_gemma":[0.00002639463,0.0001212742,0.00009054272,0.0001000306,0.00008323081,0.0001514968,0.00004030276,0.00003314087,0.000016625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002727704,"about_ca_system_score_gemma":0.00002953725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000175786,"about_ca_topic_score_gemma":0.00002667655,"domain_scores_codex":[0.998833,0.000003497008,0.0003333556,0.000372129,0.0001700062,0.0002880351],"domain_scores_gemma":[0.9986467,0.00002066428,0.0001907066,0.0009821872,0.00008365395,0.00007609311],"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":[0.000007440156,0.000012474,0.00009952427,0.00004872548,0.000008473024,0.000002382355,0.00003088355,0.0009984367,0.983967,0.00007006608,0.01438165,0.0003729178],"study_design_scores_gemma":[0.0001761162,0.00001457123,0.0008661111,0.00003763209,0.00001442324,0.00000689709,0.000007352745,0.000605169,0.9281326,0.00983585,0.0601365,0.000166761],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820101,0.0001026477,0.0009780516,0.00001597046,0.008514446,0.0005022484,0.000007767448,0.000204889,0.007663864],"genre_scores_gemma":[0.9957554,0.00000702119,0.001571849,0.000003545886,0.0002291681,0.000203284,0.00008328214,0.0000254734,0.002120965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05583441,"threshold_uncertainty_score":0.6109722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01298322514920152,"score_gpt":0.2214493802953435,"score_spread":0.208466155146142,"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."}}