Environmental and Economic Impacts of Biological Nitrogen‐Fixing (BNF) Cereal Crops
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
The global population is estimated to reach 9 to 11 billion by 2050, which will challenge our ability to produce enough nutritional food (Godfray et al., 2010). Agriculture is further challenged by global climate change, water shortages, decreasing amounts of arable land, and competition for food crops by livestock feed and biofuel crops. As well, we have an unequal global distribution of essential plant nutrients, such as nitrogen (N), where some regions have access to N fertilizers, but other regions do not. The excess N fertilizer is susceptible to loss to the plant, resulting in N pollution. The N-poor regions suffer from low crop yields, resulting in poverty and malnutrition. We need to address the agricultural problems of today and tomorrow in a more environmentally and economically sustainable way. One method to do this is to develop cereal crops that can fix their own nitrogen from the freely available N2 in our atmosphere.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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