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Record W2799725891 · doi:10.5260/chara.18.3.25

Directory of Open Access Journals (DOAJ)

2017· article· en· W2799725891 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

VenueThe Charleston Advisor · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicAcademic Publishing and Open Access
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsDirectoryComputer scienceWorld Wide WebOperating system

Abstract

fetched live from OpenAlex

DOAJ is a unique search service for fully Open Access (OA) (no embargo) peer-reviewed scholarly journals, featuring options to include article or journal level metadata in other library search services. DOAJ’s over 9,000 journals represents about 27% of the world’s scholarly peer-reviewed journals, up from 10% in 2007, and the article-level search encompasses about 10% of global scholarly journal article production. All academic disciplines are represented; some (notably medicine), more so than others. With 128 countries and many languages represented, DOAJ is diverse and inclusive. DOAJ has a well-designed, clean, attractive, easy-to-use search interface. Suggestions for improvement include more reader-friendly organisation, and results-level metadata export for journals and articles. ADA compliance checking is currently in progress. DOAJ’s application form is long and complex and could benefit from streamlining. DOAJ is the premium venue for authors seeking quality Open Access journals to publish in. Its value for finding academic material is strong and growing. It is also a must-have for libraries. DOAJ membership for libraries, while optional, is of value to libraries for local OA promotion as well as promotion of the library through DOAJ’s popular website.

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)0.012
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0150.010
Open science0.0430.007
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.487
GPT teacher head0.602
Teacher spread0.115 · 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