Bibliographic record
Abstract
1. Thermal properties and ice crystal development in frozen foods (Dr Paul Nesvadba, Rubislaw Consulting Ltd, Aberdeen, UK). 2. Effects of freezing on nutritional and microbiological properties of foods (Mark Berry, John Fletcher, Peter McClure, Joy Wilkinson, Unilever PLC, Sharnbrook, Bedfordshire, UK). 3. Modelling of freezing processes (Q. Tuan Pham, School of Chemical Sciences and Engineering, University of New South Wales, Sydney, Australia). 4. Specifying and selecting refrigeration and freezer plant (A. Pearson, Star Refrigeration, Glasgow, UK). 5. Emerging and novel freezing processes (Dr Kostadin Fikiin, Refrigeration Science and Technology, Technical University of Sofia, Bulgaria). 6. Freezing of meat (Professor Steve James, Food Refrigeration and Process Engineering Research Centre (FRPERC), Langford, North Somerset, UK). 7. Freezing of fish (Ola M. Magnussen, Anne K. T. Hemmingsen, Vidar Hardarsson and Tom S. Nordtvedt, SINTEF Energy Research, Trondheim, Norway Trygve M. Eikevik, Norwegian University of Science and Technology, Trondheim, Norway). 8. Freezing of fruits and vegetables (Cristina Luisa Miranda Silva, Elsa Margarida Goncalves & Teresa Ribeiro da Silva Brandao, Escola Superior de Biotecnologia, Universidade Catolica Portuguesa, Porto, Portugal). 9. Freezing of bakery and dessert products (Professor Alain LeBail, ENITIAA (Ecole Nationale D'Ingenieurs des Techniques des Industries Agricoles et Alimentaires), Nantes, France Dr H. Douglas Goff, Department of Food Science, University of Guelph, Ontario, Canada). 10. Developing frozen products for the market and the freezing of ready-prepared meals (Dr Ronan Gormley, Ashtown Food Research Centre (Teagasc), Ashtown, Dublin, Ireland). 11. Frozen storage (Dr Noemi E. Zaritzky, CIDCA (Centro de Investigacion y Desarrollo en Criotecnologia de Alimentos), Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Argentina). 12. Freeze drying (A.G.F. Stapley, Department of Chemical Engineering, Loughborough University, UK). 13. Frozen food transport (Dr Girolamo Panozzo, Director of Research, Construction Technologies Institute - Italian National Research Council (ITC-CNR), Padova, Italy). 14. Frozen retail display (Professor Giovanni Cortella, Department of Energy Technologies, University of Udine, Italy). 15. Consumer handling of frozen foods (Onrawee Laguerre, Refrigerating Process Research Unit, Cemagref, Antony, France).
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.062 | 0.044 |
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".