Códigos, usos y nervios: tres momentos en la construcción de un patrimonio común
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Crop biotechnology is being used in two major ways to enhance human nutrition: to improve global food security by making more food available, especially locally grown and familiar foods in the developing world, and by enhancing the nutritional composition of foods that would interest both the developed and developing worlds. Since the first commercialized products of biotechnology are major commodity crops grown primarily in the US, Canada and Argentina (soybeans, corn, canola and cotton), there is concern about whether and when crop biotechnology will help the developing world. There are, however, several on-going projects in Africa, SE Asia and Latin America where crop biotechnology is being used to enhance locally grown crops. The expectation is that genetically improved crops, e.g., those able to resist local pests, will allow even small-scale farmers to grow more crops using fewer inputs and in an environmentally sustainable manner. Furthermore, there are numerous on-going projects to enhance the nutritional or health value of foods via transgene technology. A few of these projects are described in this article.
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.
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 | 0.001 | 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 | 0.001 | 0.002 |
| 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 it