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Record W4234578287 · doi:10.5539/ijc.v8n1p203

Reviewer Acknowledgements for International Journal of Chemistry, Vol. 8, No. 1

2016· article· en· W4234578287 on OpenAlexvenueno aff
Albert John

Bibliographic record

VenueInternational Journal of Chemistry · 2016
Typearticle
Languageen
FieldChemistry
TopicFerrocene Chemistry and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryEditorial boardLibrary scienceEngineering ethicsEngineeringComputer science

Abstract

fetched live from OpenAlex

International Journal of Chemistry wishes to acknowledge the following individuals for their assistance with peer review of manuscripts for this issue. Their help and contributions in maintaining the quality of the journal is greatly appreciated.Many authors, regardless of whether International Journal of Chemistry publishes their work, appreciate the helpful feedback provided by the reviewers. Reviewers for Volume 8, Number 1 Adel F. ShoukryAhmad GaladimaAna Sanches-SilvaGreg PetersHo Soon MinJiajue ChaiK. Ishara SilvaKhaldun Al AzzamLeiming WangMadduri SrinivasaraoPankaj SharmaPraveen KumarQun YeRabia RehmanSaroj Kumar PandaSeverine QueyroySie-Tiong HaSitaram AcharyaVahid HejaziZhixia Liu Albert JohnOn behalf of,The Editorial Board of International Journal of ChemistryCanadian Center of Science and Education

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)0.025
metaresearch head score (Gemma)0.253
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.253
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.003
Science and technology studies0.0040.002
Scholarly communication0.0080.005
Open science0.0030.003
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0630.038

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 head0.016
GPT teacher head0.300
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainEvaluation
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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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