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Record W2994893201 · doi:10.1021/cen-09415-acsnews002

<i>ACS Omega </i>selects global team of editors

2016· article· en· W2994893201 on OpenAlexaboutno aff
Linda Wang

Bibliographic record

VenueC&EN Global Enterprise · 2016
Typearticle
Languageen
FieldMedicine
TopicScience, Research, and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsOmegaPhysics

Abstract

fetched live from OpenAlex

A diverse team of global experts has been selected to lead ACS Omega, the American Chemical Society’s newest open access journal publishing peer-reviewed articles. Based in the Americas, Europe, India, and China, the editors not only represent key geographic regions of active R&D, but they also bring expertise from four distinct scientific areas of interest. The new editors are Cornelia Bohne, a professor of chemistry at the University of Victoria in Canada; Krishna Ganesh, director of the Indian Institute of Science Education & Research (IISER) in Pune, India; Luis Liz-Marzán, Ikerbasque research professor and scientific director at Centre for Cooperative Research in Biomaterials (CIC biomaGUNE) in Spain; and Deqing Zhang, director of the Institute of Chemistry, Chinese Academy of Sciences, in China. Bohne’s research focuses on developing the fundamental understanding of the dynamics of supramolecular systems and on applying this knowledge to functional supramolecular materials. Ganesh is an expert in

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.111
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.308
Teacher spread0.300 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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