{"id":"W2579943635","doi":"10.1142/s0218339017500061","title":"JOINT IMPACTS OF THERAPY DURATION, DRUG EFFICACY AND TIME LAG IN IMMUNE EXPANSION ON IMMUNITY BOOSTING BY ANTIVIRAL THERAPY","year":2017,"lang":"en","type":"article","venue":"Journal of Biological Systems","topic":"Immune Cell Function and Interaction","field":"Immunology and Microbiology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Tongji University; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Immunity; Immune system; Boosting (machine learning); Immunology; Phase lag; Lag; Medicine; Pharmacotherapy; Artificial intelligence; Computer science; Internal medicine; Mathematics","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":[0.001295041,0.0001581591,0.000521515,0.000108618,0.0002579038,0.00005156129,0.0001978797,0.0002158955,0.00009380353],"category_scores_gemma":[0.0004030023,0.00009384231,0.0001131514,0.00004089085,0.0001579778,0.0002101556,0.00003877721,0.0004533318,0.00002856421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004006287,"about_ca_system_score_gemma":0.00002317948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002993508,"about_ca_topic_score_gemma":8.898846e-7,"domain_scores_codex":[0.9981177,0.0006489739,0.0008708905,0.0001284109,0.00005193466,0.0001820673],"domain_scores_gemma":[0.997996,0.0002388929,0.001379723,0.0002270453,0.0001386981,0.00001960209],"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":[0.00168605,0.0003074038,0.005531705,0.000005667888,0.00007493738,0.000002804139,0.0002441753,0.000002091151,0.9858585,0.00002005461,0.001330203,0.004936425],"study_design_scores_gemma":[0.006203603,0.003623426,0.3626268,0.0004992299,0.000007232135,0.0001583984,0.0004761783,0.00002067563,0.6165637,0.00002010509,0.009598311,0.0002023216],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890119,0.008729582,0.0000101498,0.0002282668,0.001356327,0.0002208665,0.000003078654,0.000009437161,0.0004303445],"genre_scores_gemma":[0.9963837,0.003054979,0.000003906646,0.00004466498,0.00005147217,0.000002125183,0.00001560202,0.000007061591,0.0004364564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3692948,"threshold_uncertainty_score":0.3826779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0319930630628246,"score_gpt":0.2680472022237262,"score_spread":0.2360541391609016,"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."}}