{"id":"W4282834074","doi":"10.1093/bioinformatics/btac391","title":"SPEAR: Systematic ProtEin AnnotatoR","year":2022,"lang":"en","type":"article","venue":"Bioinformatics","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Réseau Québécois de Recherche sur les Médicaments","keywords":"Spear; Python (programming language); Computer science; Annotation; Documentation; Visualization; Computational biology; Data mining; Biology; Programming language; Artificial intelligence; Archaeology","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":[0.0004177584,0.0001702088,0.0002100479,0.00006966233,0.0002869132,0.00006028168,0.0003828298,0.00005052767,0.00007067077],"category_scores_gemma":[0.00006148069,0.000151028,0.0001133352,0.0001571389,0.00002371777,0.00001274078,0.000431301,0.0001273599,0.00007128304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003156927,"about_ca_system_score_gemma":0.00008221167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003100597,"about_ca_topic_score_gemma":6.998944e-7,"domain_scores_codex":[0.9987392,0.00004686449,0.0005557652,0.000107429,0.0002801125,0.0002705805],"domain_scores_gemma":[0.9991046,0.000005775426,0.0002535734,0.0005245103,0.00004423389,0.00006736472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001690112,0.00323165,0.004187547,0.1816929,0.003782548,0.00005772015,0.03267964,0.0129473,0.3929169,0.03768656,0.3158956,0.01323146],"study_design_scores_gemma":[0.01022396,0.007970562,0.0008848719,0.001858907,0.0004858262,0.001882041,0.09388746,0.2281416,0.1184831,0.0008649807,0.5294285,0.005888213],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9667456,0.001473855,0.006746652,0.0003045125,0.0005368706,0.003134693,0.000152741,0.0001145389,0.02079059],"genre_scores_gemma":[0.9842852,0.00003108054,0.01094343,0.0005839544,0.0001083888,0.0004637963,0.0003475149,0.00003999956,0.003196644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2744338,"threshold_uncertainty_score":0.6158744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01109017857965561,"score_gpt":0.210496385831353,"score_spread":0.1994062072516974,"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."}}