Infiltration experiments with ultra-high spatial and temporal resolution of saturation measurements
Bibliographic record
Abstract
Near surface hydrological processes whereby moisture exchange occurs between the vadose zone and above-ground weather systems occur on daily, seasonal, and long-term cycles. Well-controlled laboratory studies of near surface moisture migration are often limited due to number of measurement points of moisture content and pore pressure. This presentation will describe experimental and digital image analysis techniques incorporating a refractive index matched soil-pore fluid combination that increase spatial resolution of saturation measurements by over 6 orders of magnitude. The refractive index matched material changes color from black (Saturation=1) to white (Saturation=0) allowing for saturation measurements at the digital pixel scale. This visualization technique allows for direct observation of flow effects which affect boundary measurements and local flow mechanisms. The capabilities of unsaturated transparent soil are incorporated in a 2D infiltration apparatus to examine the influence of confined air on infiltration. 2D experiments agree with previous column infiltration results showing air confinement decreases infiltration rate by more than one half. The 2D apparatus allows a clear unstable wetting front to develop, visualization of dynamic moisture migration within the transmission zone. In addition, the high spatial resolution saturation measurements show detectable influence of thin heterogeneities on wetting front migration and the influence of flow direction on saturation distribution. The high-resolution saturation measurements will allow for calibration of computational models multi-phase flow and open up new insight into near surface processes to improve water balance calculations and soil-structure-climate interactions.
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.
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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".