Bibliographic record
Abstract
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 7, Number 1Alex Augusto Gonçalves, Federal Rural University of Semi-Arid (UFERSA), BrazilBojana Filipcev, University of Novi Sad, SerbiaComan Gigi, Dunarea de Jos University of Galati, RomaniaCorina-aurelia Zugravu, University of Medicine and Pharmacy Carol Davila, RomaniaDiego A. Moreno-Fernández, CEBAS-CSIC, SpainEfstathios S Giotis, Royal Veterinary College, United KingdomElke Rauscher-Gabernig, Austrian Agency for Health and Food Safety, AustriaGisele Fátima Morais Nunes, Federal Center of Technological Education of Minas Gerais, BrazilIsabela Mateus Martins, State University of Campinas, BrazilJose M. Camina, National University of La Pampa and National Council of Scientific and Technical Researches (CONICET), ArgentinaJose Maria Zubeldia, Gestión Sanitaria de Canarias – Gobierno de Canarias, SpainJuliano De Dea Lindner, Federal University of Santa Catarina (UFSC), BrazilLenka Kourimska, Czech University of Life Sciences Prague, Czech RepublicLuis Patarata, Universidade de Trás-os-Montes e Alto Douro, PortugalMamdouh El-Bakry, Cairo University, EgyptMarco Iammarino, Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, ItalyMulunda Mwanza Mulunda, School of Agriculture North West University, South AfricaNingning Zhao, Oregon Health & Science University, United StatesQinlu Lin, Central South University of Forestry and Technology, ChinaSachin Kumar Samuchiwal, Harvard Medical School, Harvard University, United StatesSonchieu Jean, University of Bamenda, CameroonTinna Austen Ng'ong'ola-Manani, Lilongwe University of Agriculture & Natural Resources, MalawiXingjun Li, Academy of the State Administration of Grains, ChinaXinyin 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 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 | 0.058 | 0.432 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.109 | 0.071 |
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".