Effects of long-term tillage, terminating no-till and cropping system on organic C and N, and available nutrients in a Gleysolic soil in Québec, Canada
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
Abstract Some biological and chemical properties of a Gleysol were examined after 24 years of soil tillage (chisel plough – CP, mouldboard plough – MP, no-till – NT) and that of ploughing the 24-yr NT (P-NT) once, in two cropping systems (conventional – CONV, organic – ORG) applied over 4 years (2007–2010) of a long-term experiment (autumn 1987–autumn 2011) at La Pocatière, Québec, Canada. The 0–10, 10–20 and 20–30 cm soil depths were sampled in autumn 2011 after a maize trial. Tillage affected light fraction organic carbon (LFOC), light fraction organic nitrogen (LFON) and mineralizable N (N min ) in soil, with the lowest LFOC, LFON and N min values in the MP treatment. No-till had lower soil pH than the other tillage systems in the 10–20 and 20–30 cm soil depths. Tillage affected the amounts of nitrate-N in 0–10 and 10–20 cm soil depths, with the lowest amounts for MP (4.3 kg nitrate-N/ha) compared with NT (7.2 or 8.5 kg nitrate-N/ha) or CP (7.7 kg nitrate-N/ha). The P-NT had no negative impact on organic C and N, or available nutrients in soil. Cropping system had no effect on soil organic C and N, available nutrients or pH. Findings suggest that long-term NT or CP may result in greater storage of organic C and N in soil and improve available nutrients compared with MP. Ploughing 25-year-old NT plots redistributed available nutrients in the profile but had no negative effect on soil organic C or N.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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