{"id":"W2089581494","doi":"10.3390/vaccines3020293","title":"Measuring Cellular Immunity to Influenza: Methods of Detection, Applications and Challenges","year":2015,"lang":"en","type":"review","venue":"Vaccines","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Medical Research Council Canada","keywords":"Vaccination; Immunity; Immunology; Virology; Pandemic; Immune system; Vaccine efficacy; Biology; Antigen; Antigenic variation; Influenza A virus; Virus; Herd immunity; Antigenic drift; Disease; Medicine; Coronavirus disease 2019 (COVID-19); Infectious disease (medical specialty)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001675587,0.0003517473,0.001911909,0.0005825799,0.0001230628,0.00001296722,0.0002111047,0.0002187718,0.000009962582],"category_scores_gemma":[0.001119552,0.0002639238,0.0001950302,0.000585341,0.00004632465,0.00005178665,0.0003960794,0.0004123082,0.000035884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001262478,"about_ca_system_score_gemma":0.0002217671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007062378,"about_ca_topic_score_gemma":0.0000206427,"domain_scores_codex":[0.9980003,0.0003821005,0.0006515993,0.0003757124,0.0003107206,0.0002795323],"domain_scores_gemma":[0.9975659,0.0003578143,0.0002310736,0.0007625762,0.0008505306,0.0002320726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002494533,0.00004007175,0.000008179557,0.03158804,0.0003541398,0.000001254323,0.0002009417,3.003244e-7,0.000104091,0.00002928009,0.00003991483,0.9676088],"study_design_scores_gemma":[0.0002796272,0.0001348373,0.00009379421,0.00306923,0.0007462921,0.00002063905,0.0001260702,9.188885e-7,0.0004403718,0.00005983593,0.994832,0.0001964285],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002975918,0.9965001,0.0005217609,0.00006077651,0.00005210311,0.001968223,0.00001616075,0.00006319213,0.0007879468],"genre_scores_gemma":[0.000008323032,0.9940456,0.004653698,0.00002582859,0.000231787,0.0008851818,0.000005120789,0.00005447958,0.00008993923],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.994792,"threshold_uncertainty_score":0.9999813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4919264911759235,"score_gpt":0.501027918934406,"score_spread":0.009101427758482494,"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."}}