Bibliographic record
Abstract
This paper presents an evaluation of the soil hydraulic parameters (SHP) for a mountainous podzolic soil profile. Due to the tickness of the top-soil layer only the SHPs for the lower layers can be identified using standard approaches – a single ring (SR) infiltration experiment and a Guelph permeameter (GP) measurement.The SHPs for the top soil layer were identified here by inverse modeling of the SR infiltration process, where, especially, the initial unsteady part of the experiment can provide very useful data for evaluating the retention curve parameters and the saturated hydraulic conductivity. This inverse analysis is the main topic of this paper. Since the infiltration process is a typical case of a model that describes the progressive breakthrough of the wetting curve, we made use of adaptive domain decomposition (dd-adaptivity) described by [1, 2, 3] for sequential activation and deactivation of the segments of our computational domain. Finally, we conducted a sensitivity analysis of our objective function on the SHP set.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".