A study of spatial variability of the physical, chemical and biological\nproperties of two agricultural soils for site specific fertilization\nmanagement
Bibliographic record
Abstract
A study was carried out at the IRDA's Experimental Farm, located in\nSaint-Lambert de Lauzon (Quebec, Canadá). Two Gleysols were\nselected (frigid Aeric Haplaquept), soil A belongs to Le Bras series,\nsilty loam, imperfectly drained and with a deep loamy clay horizon.\nSoil B belongs to Le Bras series, with coarse sandy and skeletal\ntexture. The size of the experimental plots was about 4000 m2 each. In\nearly spring soil samples were taken in a 10 x 10 m grid resulting in\nforty sample sites. Two kinds of samples were taken, one of the\ntoplayer between 0 and 20 cm and the other of each 10 cm. between 0 and\n40 cm. Nitrogen mineralization potential, soil respiration, enzyme\nactivity, texture, bulk density, pH (1:2), total nitrogen, N-NH4,\nN-NO3, organic carbon, available phosphorus, exchangeable potassium,\ncalcium and magnesium of the samples taken from the toplayer and bulk\ndensity, organic carbon and total nitrogen of the samples from each ot\nthe 10 cm. layers were determined. Geostatistical analysis was\nperformed by GS+ software (Gamma Design Software, 2000). Spatial\ndistribution maps of soil properties were made by interpolation\n(kriging). Spatial variability of bulk density and organic carbon\nshowed a close relationship, even in deep horizons. Total nitrogen, C/N\nand nitrogen mineralization potential, nitrates and soil respiration\nshowed a spatial distribution pattern likes organic carbon spatial\ndistribution.
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) | 0.000 | 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 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".