{"id":"W4412744441","doi":"10.2196/66551","title":"Estimating the Population Size of People Who Inject Drugs in 3 Cities in Zambia: Capture-Recapture, Successive Sampling, and Bayesian Consensus Estimation Methods","year":2025,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mark and recapture; Population; Statistics; Estimation; Population size; Bayesian probability; Small area estimation; Sampling (signal processing); Medicine; Demography; Estimator; Geography; Econometrics; Environmental health; Computer science; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00313197,0.0001716613,0.0005323487,0.0002503848,0.0001747039,0.00007386087,0.00008217101,0.000125065,0.000006318647],"category_scores_gemma":[0.00480515,0.0001427419,0.00002937157,0.0007032649,0.00007081129,0.0001322243,0.00004467434,0.000236053,9.09407e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001050959,"about_ca_system_score_gemma":0.000243309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004857156,"about_ca_topic_score_gemma":0.007341065,"domain_scores_codex":[0.9975919,0.0007861989,0.0008591011,0.0002701036,0.0001793383,0.0003133737],"domain_scores_gemma":[0.995345,0.003765285,0.0004686578,0.0002139628,0.0001167938,0.0000902813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003279929,0.00004008089,0.9130391,0.001091127,0.000008658094,2.674912e-7,0.01162389,0.0007593048,0.000002363499,0.02348193,0.0001425193,0.04977794],"study_design_scores_gemma":[0.0004959265,0.00001886905,0.7094113,0.0001320005,8.812984e-7,0.000003211728,0.0009390314,0.2649776,5.464582e-7,0.02387469,0.00004587483,0.0001000754],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.945738,0.0006743963,0.04521894,0.006997578,0.0001566486,0.0008878306,0.00002254697,0.00004170828,0.0002623327],"genre_scores_gemma":[0.9447008,0.00002264368,0.05481965,0.0002675781,0.00001959014,0.00006300189,0.00004890626,0.00001177315,0.00004601139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2642183,"threshold_uncertainty_score":0.73426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03698335080622499,"score_gpt":0.3895836347747608,"score_spread":0.3526002839685358,"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."}}