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Bibliographic record
Abstract
\nOur 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.\n \n\nCodex Alimentarius Packed with corporates (above) Elisabeth Sterken\nGlobal Nutrition Report The world seen from the top Sabah Benjelloun\nVisions We all need to aspire José Luis Vivero Pol, Mark Wahlqvist\nFood as commons Can food be a public good? George Kent\nIron supplementation Good food is best Kaleab Baye\nAgroecology Real Farming Colin Tudge\nVitamin A supplementation From fiasco to scandal Ashok Bhurtyal\nVitamin A supplementation Tipping the point Geoffrey Cannon\n
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".