{"id":"W2035743530","doi":"10.1002/sim.2816","title":"HIV viral dynamic models with dropouts and missing covariates","year":2007,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"HIV Research and Treatment","field":"Immunology and Microbiology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Covariate; Missing data; Dropout (neural networks); Human immunodeficiency virus (HIV); Drop out; Viral load; Medicine; Set (abstract data type); Econometrics; Statistics; Computer science; Immunology; Mathematics; Machine learning","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":[0.02831081,0.00157503,0.004073485,0.001424961,0.001203299,0.002290688,0.003801156,0.003096215,0.006420369],"category_scores_gemma":[0.05872632,0.001011685,0.00235562,0.002317454,0.002412172,0.002964249,0.002660371,0.004372075,0.0008398572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001838784,"about_ca_system_score_gemma":0.001757637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01414919,"about_ca_topic_score_gemma":0.006257451,"domain_scores_codex":[0.9935517,0.004387846,0.0002510498,0.0006190132,0.0004824127,0.0007078453],"domain_scores_gemma":[0.9441085,0.04423526,0.006176068,0.002205133,0.002109968,0.001164942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001384373,0.000369288,0.02137401,0.0004232485,0.0004460248,0.001162727,0.0008308478,0.7832322,0.0003453064,0.1481739,0.004938379,0.03731979],"study_design_scores_gemma":[0.0003731645,0.0002552293,0.002272061,0.000083442,0.0001250421,0.0001438057,0.0001628575,0.9093447,0.0002081121,0.08484282,0.002131833,0.00005704551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3454062,0.003806964,0.6341336,0.005618047,0.0005436058,0.0009128514,0.003860403,0.0007120968,0.005006163],"genre_scores_gemma":[0.9104448,0.002588702,0.06275357,0.0009405684,0.0004196129,0.00128873,0.002795728,0.0001050956,0.01866325],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02831081,"threshold_uncertainty_score":0.1497236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01221600939019311,"score_gpt":0.3083770029980744,"score_spread":0.2961609936078813,"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."}}