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Record W4253536307 · doi:10.1002/cyto.a.23582

Issue Information – Editorial board & Publication schedule

2018· paratext· en· W4253536307 on OpenAlexaffabout
Attila Arnok, Ryan R. Brinkman, Antonio Cosma, Zbigniew Darżynkiewicz, Donna J. Arndt‐Jovin, Markus J. Barten, Ewert Bengtsson, Meredith Calvert, Andrea Cossarizza, Sándor Damjanovich, Elena Holden, James R. Jett, William J. Karpus, Awtar Krishan, Gerard Lizard, Stephen J. Lockett, B Ela, Moln Ar, Robert F. Murphy, Gerhard Nebe‐von‐Caron, John P. Nolan, Gustavo K. Rohde, Herbert Schneckenburger, Larry A. Sklar, Xuantao Su, Frank Founding Editor, Brian H. Mayall

Bibliographic record

VenueCytometry Part A · 2018
Typeparatext
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsEditorial boardCitationComputer scienceScheduleInformation retrievalLibrary scienceWorld Wide WebData science

Abstract

fetched live from OpenAlex

Clinical Cytometry as part of their membership dues.Wiley's Corporate Citizenship initiative seeks to address the environmental, social, economic, and ethical challenges faced in our business and which are important to our diverse stakeholder groups.Since launching the initiative, we have focused on sharing our content with those in need, enhancing community philanthropy, reducing our carbon impact, creating global guidelines and best practices for paper use, establishing a vendor code of ethics, and engaging our colleagues and other stakeholders in our efforts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.211
Threshold uncertainty score0.301

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0030.001
Scholarly communication0.0100.005
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.7890.845

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 head0.037
GPT teacher head0.250
Teacher spread0.213 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2018
Admission routes2
Has abstractyes

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Same venueCytometry Part ASame topicDiverse Scientific and Economic StudiesFrench-language works237,207