MétaCan
Menu
Back to cohort
Record W4392717126 · doi:10.1016/s2472-5552(24)00013-3

Publisher's Note

2024· article· en· W4392717126 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

VenueSLAS DISCOVERY · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicAcademic Publishing and Open Access
Canadian institutionsDiscovery Centre
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Within the publishing industry, article numbering has emerged as an easy and efficient way to cite journal articles. Elsevier has successfully rolled out article numbering to its multidisciplinary open access journal, Heliyon, along with more than 1600 other journals, and the academic community has responded positively to this initiative. Building upon the positive feedback, we are thrilled to announce the introduction of article numbering to SLAS Discovery, effective February 2024. A unique article number is an abbreviated form of an article's DOI - digital object identifier. Citing an article with an article number is very simple: the article number is used instead of the page range in the citation.[2]Van der Geer J, Hanraads JAJ, Lupton RA. The art of writing a scientific article. Heliyon. 2018; 19:100205. https://doi.org/10.1016/j.heliyon.2018.100205. Journal volumes and issue numbers will remain in place. However, SLAS Discovery will now use article numbering to identify specific articles. Introducing article numbers brings several benefits for the journal and its readers and authors. •More flexible reading: Article content can be optimized based on the device used to access it, supporting reading on-the-move, without needing to know how many traditional print pages the article takes up.•Increased options for grouping related content: In online collections and Special Issues, articles can now be placed in any order, helping readers identify papers relevant to their research interests faster.•Faster publication: With article numbers, the version of record of the article is online and citable as soon as the proof corrections are incorporated, ensuring readers have access to the latest research faster. We are delighted that SLAS Discovery's readers and authors will now enjoy these benefits.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.759
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0210.017
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.067
GPT teacher head0.412
Teacher spread0.345 · 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