Smart Motions: Reducing the effect of parameter uncertainties during feedforward control of a robotic manipulator
Bibliographic record
Abstract
Saturated soil paste extracts indicate soluble ions in soil pore water that are available to vegetation. As such, they are thought to accurately describe the relationship between soil and groundwater salinity. To test this assumption, soil and groundwater samples were collected from 575 monitoring wells in saline regions of the Western Canadian Sedimentary Basin (WCSB). Samples were analyzed for electrical conductivity (EC) and Cl<sup>-</sup>, Na<sup>+</sup>, Ca<sup>2+</sup>, Mg<sup>2+</sup>, K<sup>+</sup>, SO<sup>42-</sup>, and HCO<sup>- 3</sup> content. We compared groundwater ionic concentrations to paste extracts derived from matching soils, finding that differences from in situ soil porosity cause saturated pastes to underestimate groundwater salinity. Therefore, we provide pedotransfer functions for accurately calculating groundwater quality from soil data. In addition, we discuss the effects of porosity and soil composition on the saturated paste method, as measured through hydraulic conductivity, saturation percent, and sample lithology. Groundwater salinity may also influence further leaching of salts from soil. As produced water (NaCl brine) spills are common across the sulfate-rich soils of the WCSB, we considered the effects of NaCl on leaching of other ions, finding that influx of Na<sup>+</sup> into groundwater is associated with increased sulfate leaching from soil. Therefore, considering the secondary effects of produced water on groundwater quality is essential to spill management.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".