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Retractions and Corrections at Scholars Portal Journals

2023· article· en· W4385386714 on OpenAlexaffabout
Jessica Hymers, Qiuting Lin

Bibliographic record

VenueBalisage series on markup technologies · 2023
Typearticle
Languageen
FieldComputer Science
TopicLibrary Science and Information Systems
Canadian institutionsOntario Council of University Libraries
Fundersnot available
KeywordsMetadataComputer scienceWorkflowIdentifierWorld Wide WebXMLProcess (computing)Digital libraryService (business)Object (grammar)Information retrievalLibrary scienceDatabaseBusiness

Abstract

fetched live from OpenAlex

Scholars Portal Journals, a service of the Ontario Council of University Libraries (OCUL), is an XML based repository that hosts e-journal content for universities in Ontario. As part of the OCUL mission to provide accurate and up-to-date access to scholarly research, Scholars Portal has recently taken on a project to improve how article corrections and retractions are handled in our workflow. This paper introduces the new process of utilizing the JATS metadata element to link between articles and their corrections and retractions so that users are immediately aware that there have been changes to the article they are viewing. This paper will also discuss challenges in this process including the inability to handle articles that have not been registered with a Digital Object Identifier (DOI) and difficulties with inconsistent use of attribute values.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchResearch integrity
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptResearch integrityScholarly communication
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.079
metaresearch head score (Gemma)0.453
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.417

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0790.453
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0270.020
Science and technology studies0.0120.005
Scholarly communication0.0210.012
Open science0.0040.013
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0650.066

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 head0.026
GPT teacher head0.256
Teacher spread0.231 · 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

Labeled directly by 2 models reading the full record.

MetaresearchResearch integrityScholarly communication

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
DomainEvaluation
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
Published2023
Admission routes2
Has abstractyes

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