Bibliographic record
Abstract
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 find the application form and details at http://recruitment.ccsenet.org and e-mail the completed application form to jfr@ccsenet.org.Reviewers for Volume 6, Number 6Adele Papetti, University of Pavia, ItalyAlexandrina Sirbu, Constantin Brancoveanu University, RomaniaAmin Mousavi Khaneghah, State University of Campinas, BrazilAmmar Eltayeb Ali Hassan, University of Tromsø, NorwayAnna Iwaniak, Warmia and Mazury University, PolandAntonello Santini, University of Napoli "Federico II", ItalyCheryl Rosita Rock, California State University, United StatesCristina Damian, University of Suceava, RomaniaDomitila Augusta Huber, Federal University of Santa Catarina, BrazilEganathan Palanisami, Meta Procambial Biotech Private Limited, IndiaElsa M Goncalves, Instituto Nacional de Investigacao Agrária (INIA), PortugalIsabela Mateus Martins, State University of Campinas, BrazilJintana Wiboonsirikul, Phetchaburi Rajabhat University, ThailandJose M. Camina, National University of La Pampa and National Council of Scientific and Technical Researches (CONICET), ArgentinaLenka Kourimska, Czech University of Life Sciences Prague, Czech RepublicLeonardo Martín Pérez, Pontifical Catholic University of Argentina, ArgentinaLiana Claudia Salanta, University of Agricultural Sciences and Veterinary Medicine, RomaniaLuis Patarata, Universidade de Trás-os-Montes e Alto Douro, PortugalMarco Iammarino, Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, ItalyMeena Somanchi, United States Department of Agriculture, United StatesNingning Zhao, Oregon Health & Science University, United StatesSefat E Khuda, Centre for Food Safety and Applied Nutrition, United StatesSlavica Grujic, University of Banja Luka, Bosnia and Herzegovina, Bosnia HerzegovinaSonchieu Jean, University of Bamenda, CameroonSuzana Rimac Brncic, University of Zagreb, CroatiaTzortzis Nomikos, Harokopio University, GreeceWinny Routray, McGill University, CanadaZelalem Yilma, Haramaya and Hawassa Universities, Ethiopia
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.349 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.107 | 0.067 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".