{"id":"W2337877636","doi":"10.1093/neuonc/nov204.08","title":"ATPS-08DISCOVERY OF NOVEL GLIOMA-TARGETING PEPTIDES USING A HIGH-THROUGHPUT MICROFLUIDIC MAGNETIC-ACTIVATED SORTER","year":2015,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Glioma; Peptide; Bead; Peptide library; Microfluidics; Brain tissue; Brain cancer; Chemistry; Molecular biology; Cancer research; Cancer; Nanotechnology; Biochemistry; Biology; Materials science; Neuroscience; Peptide sequence; Gene; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002612376,0.0004073164,0.0004403686,0.0004142255,0.0002437715,0.0004042173,0.0003323212,0.0004040853,0.001200128],"category_scores_gemma":[0.0002430798,0.0001439842,0.0003806375,0.0003107953,0.0001465478,0.0001950687,0.0002533449,0.0004141615,0.000572742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003420496,"about_ca_system_score_gemma":0.0004335309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005462996,"about_ca_topic_score_gemma":0.001007472,"domain_scores_codex":[0.9998013,0.00001516773,0.00001663741,0.00003567601,0.00009479396,0.00003638122],"domain_scores_gemma":[0.9999158,0.00002009524,0.00001775754,0.000007589765,0.0000161541,0.00002254857],"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":[0.0001474988,0.00006464649,0.0003720482,0.0000796682,0.0000192085,0.00007968727,0.00001949185,0.0004544601,0.989041,0.0001861403,0.0006690733,0.008866941],"study_design_scores_gemma":[0.0000452457,0.000252755,0.002065872,0.000005369051,0.00001801474,0.0002475315,0.00001490912,0.005523109,0.9859714,0.00006972492,0.005769924,0.00001607736],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9357751,0.002939426,0.05216169,0.0006332612,0.0002352816,0.0003163768,0.002584934,0.001228026,0.004125989],"genre_scores_gemma":[0.8915812,0.001882176,0.08700691,0.0007273799,0.00007541075,0.0004096098,0.005507995,0.0001347398,0.01267445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001200128,"threshold_uncertainty_score":0.00401485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0303988934859163,"score_gpt":0.3055855659847469,"score_spread":0.2751866724988306,"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."}}