Field study on macropore flow in typical Black soils of northeast China
Bibliographic record
Abstract
Jiang, X., Wang, E., Chen, X., Xia, X. and Shi, C. 2012. Field study on macropore flow in typical Black soils of northeast China. Can. J. Soil Sci. 92: 559–566. Macropores are important preferential pathways for the transport of water and contaminants in soil. A series of hood infiltration experiments were conducted using dye tracers (Brilliant Blue FCF) at pressure heads of −5.0 cm, −3.0 cm, and −1.0 cm at a conventional tilled site on Keshan Farm, northeast China. The study objective was to combine the test method of dye tracing with a hood infiltrometer to analyze soil subjected to conventional tillage methods. Dye staining patterns and macroporous networks were analyzed by excavation, mapping, photography, and image analysis. Results showed that macropore flow began very near the soil surface under three pressures heads of −5.0 cm, −3.0 cm and −1.0 cm, and that a pressure head of −1.0 cm resulted in more lateral flow. Soil deeper than 40.0 cm was less disturbed, which resulted in good continuity. At pressure heads of −5.0, −3.0 and −1.0 cm, the dye staining technique resulted in maximum stained depths of 74.3, 60.7 and 64.7 cm, respectively, with maximum stained widths of 41.6, 41.5 and 47.9 cm, respectively (at depths from 14.0 to 28.0 cm). Soil under a pressure head of −1.0 cm had the highest initial and steady infiltration rates of 13.0 and 4.1 mm min−1, respectively. Soil under a pressure head of −5.0 cm showed the most connectivity. To distinguish the macropores from the interaction area of macropore flow and the soil matrix surrounding the macropores, the stained area was separated into different classes based on dye color.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".