MétaCan
Menu
Back to cohort
Record W4249169270 · doi:10.5539/jfr.v9n2p58

Reviewer Acknowledgements for Journal of Food Research, Vol. 9 No. 2

2020· article· en· W4249169270 on OpenAlexvenueno aff
Bella Dong

Bibliographic record

VenueJournal of Food Research · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicResearch on scale insects
Canadian institutionsnot available
Fundersnot available
KeywordsLibrary sciencePolitical scienceHumanitiesAgency (philosophy)ArtSociologySocial science

Abstract

fetched live from OpenAlex

Journal of Food Research 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 are greatly appreciated. Journal of Food Research is recruiting reviewers for the journal. If you are interested in becoming a reviewer, we welcome you to join us. Please contact us for the application form at: jfr@ccsenet.org Reviewers for Volume 9, Number 2   Ammar Eltayeb Ali Hassan, University of Tromsø, Norway Ana Silva, National Institute of Health Dr Ricardo Jorge, Portugal Ancuta Elena Prisacaru, Stefan cel Mare University of Suceava, Romania Bernardo Pace, Institute of Science of Food Production (ISPA), National Research Council (CNR), Italy Bruno Alejandro Irigaray, Facultad de Química, Uruguay Coman Gigi, Dunarea de Jos University of Galati, Romania Diego A. Moreno-Fernández, CEBAS-CSIC, Spain Djilani Abdelouaheb, Badji Mokhtar University, Algeria Elke Rauscher-Gabernig, Austrian Agency for Health and Food Safety, Austria Elsa M Goncalves, Instituto Nacional de Investigacao Agrária (INIA), Portugal Essence Jeanne Picones Logan, University of Santo Tomas, Philippines Greta Faccio, Empa-Swiss Federal Laboratories for Material Sciences and Technology, Switzerland J. Basilio Heredia, Research Center for Food and Development, Mexico Jintana Wiboonsirikul, Phetchaburi Rajabhat University, Thailand Jose Maria Zubeldia, Gestión Sanitaria de Canarias – Gobierno de Canarias, Spain Luis Patarata, Universidade de Trás-os-Montes e Alto Douro, Portugal Ma Lourdes Vazquez-Odériz, University of Santiago de Compostela, Spain Marco Iammarino, Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, Italy Mariana de Lourdes Almeida Vieira, Centro Federal de Educação Tecnológica de Minas Gerais, Brazil Massimiliano Renna, CNR-National Research Council of Italy, Italy Paolo Polidori, University of Camerino, Italy Richard Nyanzi, Tshwane University of Technology, South Africa Shao Quan Liu, National University of Singapore, Singapore Stuart Munson-McGee, New Mexico State University, United States Tzortzis Nomikos, Harokopio University, Greece Xinyin Jiang, Brooklyn College, United States

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)0.037
metaresearch head score (Gemma)0.305
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 score0.963
Threshold uncertainty score0.372

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.305
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0090.004
Science and technology studies0.0050.002
Scholarly communication0.0120.006
Open science0.0040.004
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.1110.070

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 head0.333
GPT teacher head0.434
Teacher spread0.101 · 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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Food ResearchSame topicResearch on scale insectsFrench-language works237,207