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Record W2107363066 · doi:10.1002/asi.23367

The invariant distribution of references in scientific articles

2015· article· en· W2107363066 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of the Association for Information Science and Technology · 2015
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Text Analysis Techniques
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
FundersCanada Research Chairs
KeywordsBibliometricsComputer scienceScientific communicationSection (typography)Information retrievalLibrary scienceData science

Abstract

fetched live from OpenAlex

The organization of scientific papers typically follows a standardized pattern, the well‐known IMRaD structure (introduction, methods, results, and discussion). Using the full text of 45,000 papers published in the PLoS series of journals as a case study, this paper investigates, from the viewpoint of bibliometrics, how references are distributed along the structure of scientific papers as well as the age of these cited references. Once the sections of articles are realigned to follow the IMRaD sequence, the position of cited references along the text of articles is invariant across all PLoS journals, with the introduction and discussion accounting for most of the references. It also provides evidence that the age of cited references varies by section, with older references being found in the methods and more recent references in the discussion. These results provide insight into the different roles citations have in the scholarly communication process.

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)0.007
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.278
Teacher spread0.259 · 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