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Record W2800853470 · doi:10.1177/0748730418768120

A Clockwork Wikipedia: From a Broad Perspective to a Case Study

2018· article· en· W2800853470 on OpenAlexfundno aff
Omer Benjakob, Rona Aviram

Bibliographic record

VenueJournal of Biological Rhythms · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsnot available
FundersAzrieli FoundationTel Aviv University
KeywordsClockworkPerspective (graphical)Data scienceWorld Wide WebBiologyComputer scienceHistoryArtificial intelligence

Abstract

fetched live from OpenAlex

While research has shown that scientists use Wikipedia and that scientific content on Wikipedia ramifies back into scientific literature, many questions remain on how the two sides interact and through what paradigm this dynamic may be best understood. Using the circadian clock field as a case study, we discuss this scientific field's representation on Wikipedia. We traced the changes made to the articles for "Circadian clock" and "Circadian rhythm" and reviewed the debates that informed them over a span of a decade, using Wikipedia's native and third-party tools. Specifically, we focused on how groundbreaking research pertaining to the function of biological oscillators was integrated into the articles to reflect a wider paradigmatic shift within the field. We also identified the articles' main editors to detail the dynamic collective editorial process that took place during a time that saw the field undergo a fundamental change. We discuss the different concerns the academic community has with Wikipedia-specifically regarding its content and its contributors-to ask whether the online encyclopedia's open model is inherently at odds with scientific culture or whether the model could reflect science or even expand on its core values and practices such as peer review and the idea of communicating science.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.060
GPT teacher head0.417
Teacher spread0.357 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations10
Published2018
Admission routes1
Has abstractyes

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