{"id":"W4238593257","doi":"10.32920/ryerson.14668269","title":"Bio-functionalization of silicon and its applications in mammalian and cancer cell manipulation and proliferation","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Nanotechnology research and applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Silicon; Materials science; Nanotechnology; Cancer cell; Colloidal gold; Surface modification; Cell growth; Adhesion; Cell adhesion; Matrix (chemical analysis); Biophysics; Nanoparticle; Chemistry; Cancer; Biology; Optoelectronics; Composite material; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00006350098,0.0001145541,0.0001433463,0.000125325,0.0000387736,0.00003503135,0.0000398113,0.0002297885,0.0000319693],"category_scores_gemma":[0.000008550555,0.0001225549,0.00001067305,0.0001447507,0.00003243042,0.00009537404,0.00009089046,0.0001624307,3.431192e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004457869,"about_ca_system_score_gemma":0.00003208813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001219067,"about_ca_topic_score_gemma":0.0007159034,"domain_scores_codex":[0.9993696,0.00001336924,0.0002043561,0.0002414715,0.00007578328,0.00009548599],"domain_scores_gemma":[0.9996907,0.00002732766,0.00003974035,0.000127354,0.00007504421,0.00003989099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003316392,0.000333324,0.2565965,0.009354174,0.0001778096,0.000001989322,0.001325733,0.07066081,0.5541416,0.05887491,0.0002549751,0.04824497],"study_design_scores_gemma":[0.0009941489,0.00004307205,0.1590688,0.000246734,0.0000910139,0.000008200496,0.0006384224,0.5323357,0.299407,0.005394364,0.001091646,0.0006809093],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.977342,0.008179357,0.01289794,0.0002063577,0.00002261764,0.0009157104,0.00003582279,0.00007928952,0.0003208787],"genre_scores_gemma":[0.9921055,0.006442097,0.0003773872,0.000006139028,0.00002125286,0.0007004952,0.0002340062,0.00001438705,0.0000986825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4616749,"threshold_uncertainty_score":0.4997643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0178172215642654,"score_gpt":0.2592448392453001,"score_spread":0.2414276176810347,"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."}}