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Record W4410943177 · doi:10.1097/olq.0000000000002191

Cost of the GetCheckedOnline Digital Testing Program: Micro-Costing Analysis

2025· article· en· W4410943177 on OpenAlexaffabout
Wei Zhang, Chizoba Oriuwa, Hsiu-Ju Chang, Devon Haag, Heather Pedersen, Bohdan Nosyk, Mark R. Gilbert

Bibliographic record

VenueSexually Transmitted Diseases · 2025
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsCentre for Advancing Health OutcomesBC Centre for Disease ControlUniversity of British ColumbiaMcMaster UniversityTRIUMFSimon Fraser UniversityProvidence Health Care
Fundersnot available
KeywordsActivity-based costingMedicineCost analysisService (business)Economies of scaleTest (biology)Scale (ratio)Operations managementOperations researchAccountingMarketingBusinessEngineeringCartography

Abstract

fetched live from OpenAlex

ABSTRACT: GetCheckedOnline.com is a digital sexually transmitted and blood-borne infection testing service provided in British Columbia, Canada. Using a micro-costing approach, we calculated the costs during the planning, development, and implementation phases of GetCheckedOnline.com . As more sexually transmitted and blood-borne infection tests were performed, the cost per test decreased, demonstrating economies of scale.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.031
GPT teacher head0.352
Teacher spread0.320 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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