Materials for Sustained and Controlled Release of Nutrients and Molecules To Support Plant Growth
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
Controlled release fertilizers (CRFs) are a branch of materials that are designed to improve the soil release kinetics of chemical fertilizers to address problems stemming losses from runoff or other factors. Current CRFs are used but only in a limited market due to relatively high costs and doubts about their abilities to result in higher yields and increased profitability for agricultural businesses. New technologies are emerging that promise to improve the efficacy of CRFs to add additional functionality and reduce cost to make CRFs a more viable alternative to traditional chemical fertilizer treatment. CRFs that offer ways of reducing air and water pollution from fertilizer treatments, improving the ability of plants to access required nutrients, improving water retention to increase drought resistance, and reducing the amount of fertilizer needed to provide maximum crop yields are under development. A wide variety of different strategies are being considered to tackle this problem, and each approach offers different advantages and drawbacks. Agricultural industries will soon be forced to move toward more efficient and sustainable practices to respond to increasing fertilizer cost and desire for sustainable growing practices. CRFs have the potential to solve many problems in agriculture and help enable this shift while maintaining profitability.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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