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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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.003
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 head0.031
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 teacher head, 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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