Bibliographic record
Abstract
Information on liquid distribution after injection of liquid manure is important to the evaluation of injection methods and the design of injection tools. A two-dimensional numerical model was developed to predict liquid distribution in the soil around a soil pocket. Model outputs are the lateral spread (L), vertical thickness (T), and cross-sectional area (A) of the liquid infiltration zone. Values of L do not vary with injection depth, whereas T and A increase with the injection depth. These model outputs are sensitive to effective saturated soil content (the difference between saturated and initial water contents). At greater effective saturated water content, values of L, T, and A are lower. Values of L vary from 0.13 to 0.23 m, values ofT vary from 0.09 to 0.19 m for injection depths from 0.05 to 0.15 m, and values of A vary from 0.009 to 0.030 m2. The model results were compared with field measurements taken from six forage fields with sandy loam and clay soils. The model better predicts L than T and A. The relative average error between the predictions and field measurements vary from 10.3 to 101.9%.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".