{"id":"W6969063594","doi":"10.5683/sp2/pm9tab","title":"LIST-S2: pre-computed deleteriousness of all possible mutations in human (OX=9606) protein sequences","year":2019,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"UniProt; Amino acid; Protein sequencing; Mutation; Peptide sequence; Sequence (biology); Point mutation; Chromosome","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":[0.0007336924,0.003788168,0.001619058,0.002398188,0.001208127,0.001936183,0.001875345,0.001485437,0.2354887],"category_scores_gemma":[0.003282025,0.001137523,0.001905918,0.003191278,0.0002846327,0.001909861,0.001329368,0.001432743,0.1962902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001040409,"about_ca_system_score_gemma":0.001319841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004073003,"about_ca_topic_score_gemma":0.006715399,"domain_scores_codex":[0.9994766,0.00004812124,0.00004470361,0.000169762,0.0001641437,0.00009663525],"domain_scores_gemma":[0.9988686,0.0003019519,0.00009232016,0.0002013418,0.0004276314,0.0001082374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000885681,0.00009498123,0.004093935,0.001570769,0.0001236465,0.0002616223,0.00006765532,0.001651897,0.006004877,0.0007509605,0.972473,0.01202081],"study_design_scores_gemma":[0.002114679,0.000832554,0.04106069,0.0007741142,0.0003738423,0.002214427,0.000371343,0.02412749,0.0460189,0.008184241,0.8735538,0.0003739361],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005771769,0.000308844,0.003664689,0.0001334813,0.0001936235,0.00008143457,0.9474764,0.03774047,0.004629191],"genre_scores_gemma":[0.006783703,0.000161541,0.006868058,0.0001136292,0.00004596097,0.0001448278,0.976182,0.006852578,0.00284778],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2354887,"threshold_uncertainty_score":0.7877882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03335579895573557,"score_gpt":0.3179245661637393,"score_spread":0.2845687672080037,"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."}}