MétaCan
Menu
Back to cohort
Record W2984080733 · doi:10.5937/zz1903043z

The appropriate use of the Vancouver referencing style in scientific papers published in biomedical journals

2019· article· en· W2984080733 on OpenAlexaboutno aff
Dejan Živanović, Jovan Javorac

Bibliographic record

VenueZdravstvena zastita · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicAcademic Writing and Publishing
Canadian institutionsnot available
Fundersnot available
KeywordsScientific literatureBiomedicineCitationComputer scienceScientific writingStyle (visual arts)Field (mathematics)Data scienceScientific fieldScientific articleWriting styleEngineering ethicsWork (physics)Library scienceHistoryPublishingLinguisticsEngineeringPhilosophyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Appropriate literature citation in scientific articles is a necessary and extremely important segment in the writing of any scientific paper. In modern science, referencing is accepted as a standardized method for displaying sources of scientific information and ideas which made the basis for author's scientific work, accomplishing that in a unique way that must identify their scientific origin, without any potential doubt. Since its establishment in 1978, Vancouver referencing style has become one of the most commonly used uniform methods for citing literature in scientific papers in the field of biomedicine, also known as the "author-number system". Considering all the advantages of Vancouver citing method and its presence in biomedical scientific journals, the aim of this paper is to provide readers with precise and clear instructions for its correct use in the writing of the scientific text intended for publication.

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

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.229
Teacher spread0.192 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueZdravstvena zastitaSame topicAcademic Writing and PublishingFrench-language works237,207