{"id":"W2343242756","doi":"10.1038/srep24952","title":"Pronounced peptide selectivity for melanoma through tryptophan end-tagging","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Vetenskapsrådet; Nanyang Technological University; Lee Kong Chian School of Medicine, Nanyang Technological University; Knut och Alice Wallenbergs Stiftelse; International Union of Biochemistry and Molecular Biology","keywords":"Tryptophan; Peptide; Computational biology; Selectivity; Melanoma; Chemistry; Computer science; Biochemistry; Biology; Cancer research; Amino acid","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005335027,0.0001393457,0.0001323865,0.00003760284,0.0002181841,0.00008565223,0.0001372944,0.00008971974,0.00005060176],"category_scores_gemma":[0.0001896471,0.00009812947,0.0001357002,0.00009533275,0.0001506357,0.00001796913,0.00007183247,0.00003075854,0.00001588369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002675793,"about_ca_system_score_gemma":0.0001889859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001627074,"about_ca_topic_score_gemma":0.00006412704,"domain_scores_codex":[0.9984053,0.00002656458,0.0002652106,0.0007912136,0.0001736453,0.0003381121],"domain_scores_gemma":[0.9989254,0.00001426698,0.000168282,0.0006270807,0.0002045622,0.00006041129],"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":[0.00002905744,0.00003291033,0.002648761,0.000007552369,0.00002727461,0.000009477639,0.00005269454,0.000002333178,0.9693546,0.0000515826,0.02394716,0.003836614],"study_design_scores_gemma":[0.00016056,0.0001347083,0.0004435085,0.00002062596,0.000008898823,0.00007243727,0.00002053715,0.000004670499,0.7906432,0.002049762,0.2062942,0.000146929],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824936,0.0001255228,0.01224961,0.0002137687,0.002386364,0.000345581,0.00001108571,0.00002584809,0.002148618],"genre_scores_gemma":[0.9848738,0.00001061009,0.001085697,0.00007220222,0.0001992888,0.00008551,0.00006724108,0.00001564006,0.01358997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.182347,"threshold_uncertainty_score":0.4001603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0152672234292164,"score_gpt":0.2595880465756966,"score_spread":0.2443208231464802,"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."}}