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Record W4403544256 · doi:10.1186/s12939-024-02285-2

Correction: Improving accessibility to radiotherapy services in Cali, Colombia: cross-sectional equity analyses using open data and big data travel times from 2020

2024· erratum· en· W4403544256 on OpenAlexaff
Luis Gabriel Cuervo, Carmen Juliana Villamizar, Daniel Cuervo, Pablo Zapata, Maria B. Ospina, Sara Marcela Valencia, Alfredo Polo, Ángela Suárez, María Olga Bula, J. Jaime Miranda, Gynna Millán, Diana Elizabeth Cuervo Díaz, Nancy J. Owens, Felipe Piquero, Janet Hatcher Roberts, Gabriel Dario Paredes, María Fernanda Navarro, Ingrid Liliana Minotta, Carmen Palta, Eliana Martínez‐Herrera, Ciro Jaramillo Molina

Bibliographic record

VenueInternational Journal for Equity in Health · 2024
Typeerratum
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsBruyèreUniversity of OttawaQueen's University
Fundersnot available
KeywordsHealth services researchEquity (law)Open dataSocial policyCross-sectional dataPublic healthBig dataHealth informaticsCross-sectional studyBusinessEnvironmental healthMedicineComputer sciencePolitical scienceEconomicsWorld Wide WebData miningEconometricsNursing

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.005
metaresearch head score (Gemma)0.110
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: none
Teacher disagreement score0.280
Threshold uncertainty score0.558

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.110
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.007
Science and technology studies0.0030.002
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.1040.039

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 head0.774
GPT teacher head0.642
Teacher spread0.132 · 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

Citations0
Published2024
Admission routes1
Has abstractno

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