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Record W4412725883 · doi:10.1080/02763869.2025.2533771

An Analysis of the Bibliometrics of the Mexican Institute in Ophthalmology: A Case Study of an Emerging Research-Based Educational Health Institute

2025· article· en· W4412725883 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

VenueMedical Reference Services Quarterly · 2025
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Health Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBibliometricsImpact factorIndex (typography)CitationScience Citation IndexLibrary scienceMedicineCitation analysisOphthalmologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The Instituto Mexicano de Oftalmología (IMO), a non-profit eye institute, has experienced significant growth. In this case study, we analyze IMO-affiliated publications (2012-2023) and introduce the Degree of Involvement in paper authorship index (DI-index). Journal metrics were extracted from InCites Journal Citation Reports and Scimago. IMO research output grew from one publication (2012) to 31 (2023), peaking at 45 (2018). The average impact factor rose from 0.2 (2012) to 5.2 (2022). The DI-index totaled 106.6 across 227 articles. Bibliometric analysis provides valuable insights for emerging institutions, and the DI-index provides a novel approach to evaluating authorship involvement.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.031
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.240
GPT teacher head0.594
Teacher spread0.354 · 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