Effect of ignoring parameter <i>b</i> on the maximum upward flux calculated from the Gardner rational model
Bibliographic record
Abstract
Shi, W.-J., Shen, B. and Wang, Q.-J. 2014. Effect of ignoring parameter b on the maximum upward flux calculated from the Gardner rational model. Can. J. Soil Sci. 94: 97–103. The maximum upward flux (E max) of groundwater evaporation can be predicted using the Gardner model. The model is often simplified by neglecting a soil parameter (b). The paper describes methods used to assess the impact of the b parameter on predictions of E max including or eliminating b in the Gardner model. The results showed that ignoring b always resulted in a higher prediction of E max; for the same soil, the calculated E max ignoring b was higher than E bmax including b, and the difference between the measured E max and calculated E bmax was smaller. For different soils, the difference between predicted E max ignoring b and measured value increased as the soil mean particle size increased (when the water table depth was more than 1 cm). For layered soils, the measured E max was always smaller than the calculated value, regardless of whether b was included or not. And the difference between the calculated and measured values increased with increasing distance from the sandy soil interlayer in the soil profile to the water table. The main reasons for the difference between the calculated E bmax considering all parameters and the measured values are discussed based on previous research.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".