Bibliographic record
Abstract
Our final treat - a record 29 pages of letters. Team members, regular contributors, advisors and correspondents, from Canada, Morocco, Belgium, China, the US, Ethiopia, the UK, Nepal and Brazil, on food governance (Codex Alimentarius in session, below), what's wrong with the 2015 global nutrition report, the need for aspiration, food as a commons, overuse of iron supplements, and to end with a new beginning, the great vitamin A fiasco - or scandal - and the move towards universal healthy food strategies. Codex Alimentarius Packed with corporates (above) Elisabeth Sterken Global Nutrition Report The world seen from the top Sabah Benjelloun Visions We all need to aspire José Luis Vivero Pol, Mark Wahlqvist Food as commons Can food be a public good? George Kent Iron supplementation Good food is best Kaleab Baye Agroecology Real Farming Colin Tudge Vitamin A supplementation From fiasco to scandal Ashok Bhurtyal Vitamin A supplementation Tipping the point Geoffrey Cannon
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 | 0.011 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.584 | 0.434 |
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".