Water Absorption by Hydrogel Using Fertilizers
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
It was sought, in this research, to evaluate the effects of fertilizer solutions on water retention by hydrogel as well as if the application methods and fertilizers affect water retention when the hydrogel is added to the soil. In laboratory works (experiment 1), the completely randomized design was used taking into account four treatments: distilled water; Urea (UR – 2.0 g L-1 ) and Magnesium Sulfate + Monoammonium Phosphate (MS + MAP – 2.0 g L-1  each). Regarding the experiment 2, considering soil columns, a 2x3x2 factorial was used, corresponding to two hydrogel application methods: dry and mixed to the soil or diluted in water and concentrated in the center of the column; three fertilizer solutions: distilled water, UR (2.0 g L-1 ) and MS + MAP (2.0 g L-1  each) with two cycles and three repetitions. An additional witness (hydrogel free) was also added. Total water volume absorbed by hydrogel, volume stored in the soil after each cycle, pH and electrical conductivity (EC) of leached solutions were all analyzed. The MS solution was the one who impacted the most the water absorption by the hydrogel, principally when the hydrogel was not present in the soil. The pH and EC of leached solutions evidenced the fertilizer solutions salinity.
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) | 0.000 | 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) | 0.000 | 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