MétaCan
Menu
Back to cohort
Record W2069101670 · doi:10.1080/02331888.2010.500735

A GEE approach for estimating size of hard-to-reach population by using capture–recapture data

2011· article· en· W2069101670 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStatistics · 2011
Typearticle
Languageen
FieldMathematics
TopicCensus and Population Estimation
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsMark and recapturePopulation sizeStatisticsMathematicsPopulationEstimationGeeGeneralized estimating equationEconometricsDemography

Abstract

fetched live from OpenAlex

A capture–recapture estimation method for closed wildlife population has been adapted by epidemiologists to estimate the size of a hidden or hard-to-reach population. The heterogeneity of capture probabilities on the estimation of population size using capture–recapture data is considered in this article. A generalized estimating equation approach to the problem of estimating capturing probabilities is presented by considering the heterogeneity of the study population. Resulting probabilities then serve as denominators for calculating the size of the population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.933
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.201
GPT teacher head0.372
Teacher spread0.171 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it