{"id":"W2141471986","doi":"10.1006/viro.2000.0310","title":"Characterization of Murine Coronavirus Neutralization Epitopes with Phage-Displayed Peptides","year":2000,"lang":"en","type":"article","venue":"Virology","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; Armand Frappier Museum; Institut National de la Recherche Scientifique","funders":"Army Research Office; National Institute of Allergy and Infectious Diseases; Natural Sciences and Engineering Research Council of Canada; Medical Research Council Canada","keywords":"Epitope; Biology; Phage display; Virology; Monoclonal antibody; Peptide library; Neutralization; Glycoprotein; Molecular biology; Bacteriophage; Epitope mapping; Peptide; Antibody; Peptide sequence; Linear epitope; Coronavirus; Protein subunit; Virus; Conformational epitope; Gene; Biochemistry; Escherichia coli; Coronavirus disease 2019 (COVID-19); Genetics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006421,0.00009987877,0.0002434326,0.00009874313,0.00004410883,0.000004123731,0.00005971092,0.00006749316,0.002214304],"category_scores_gemma":[0.000006720063,0.00007121726,0.00003655659,0.0001769388,0.0001590472,0.00006243696,0.0000137275,0.00009744665,0.0000969688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009055449,"about_ca_system_score_gemma":0.00004321152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001081202,"about_ca_topic_score_gemma":0.00002808327,"domain_scores_codex":[0.9992455,0.00005123353,0.0001897887,0.0001655474,0.0001569672,0.0001909725],"domain_scores_gemma":[0.9996524,0.0000326091,0.00005121263,0.0001318635,0.00006043306,0.00007146094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003180336,0.0002316194,0.02524197,0.00009408168,0.00006952528,0.00009139186,0.0001518162,0.00002199447,0.94543,0.001212302,0.00004560584,0.02422936],"study_design_scores_gemma":[0.00139512,0.002131558,0.8742972,0.00004004936,0.00005382476,0.0002743311,0.0000095893,0.0004780964,0.08609547,0.00004008533,0.03507507,0.0001095994],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947509,0.00007309749,0.00007939349,0.0009227818,0.00002655935,0.0002033162,0.00002509322,0.00002413933,0.003894699],"genre_scores_gemma":[0.989562,0.0004429223,0.0001598122,0.0004818419,0.0001141154,0.00001034901,0.0002700993,0.00001415361,0.008944727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8593345,"threshold_uncertainty_score":0.9986978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02035520235194154,"score_gpt":0.2958661969804278,"score_spread":0.2755109946284862,"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."}}