Assessment of soil health by earthworm bioindicator in intensive organic farms in Quebec
Bibliographic record
Abstract
The preservation and improvement of soil health are currently major agricultural issues. Assessing the health of a soil requires the use of different indicators, earthworms are a type of bio-indicators to approach the health of a soil. Earthworms play different roles in the physical and chemical dynamics of a soil and are therefore key species for the resilience of the systems. This project aims at studying of the influence of the pedoclimatic context and of the cultural practices on 11 Quebec intensive organic farms by earthworm sampling. A physical extraction coupled with a chemical extraction with mustard were used to measure abundance and dry biomass at the group and species level inside a maize, a soybean and a cereal field for each farm. It was found that the areas studied had the characteristics of cultivated lands with a majority of endogeic and a total approaching on average 100 i.m-2. Acid soils and the intensity of tillage management (depth and frequency) are limiting factors to the development and renewal of earthworms and therefore not favorable to the health soils. The use of cover crops that are conserved or simply cut positively affects eartworms, especially juveniles. An optimum rate of soil organic matter is most often beneficial to endogeic earthworms and also promote the diversity of the earthworm species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".