Plot-scale assessment of soil freeze/thaw detection and variability with impedance probes: implications for remote sensing validation networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Several large in-situ soil moisture-monitoring networks currently exist over seasonally frozen regions that may have use for the validation of remote sensing soil freeze/thaw (F/T) products. However, further understanding of how the existing network instrumentation responds to changes in near surface soil F/T is recommended. This case study describes the results of a small plot-scale (7 × 7 m) study from November 2013 through April 2014 instrumented with 36 impedance probes. Soil temperature and real dielectric permittivity ϵr' were measured every 15 minutes during F/T transition periods at shallow soil depths (0–10 cm). Categorical soil temperature and real dielectric permittivity techniques were used to define the soil F/T state during these periods. Results demonstrate that both methods for detecting soil F/T have strong agreement (84.7–95.6%) during the fall freeze but weak agreement (53.3–60.9%) during the spring thaw. Bootstrapping results demonstrated both techniques showed a mean difference within ±1.0°C and ±1.4 ϵr' between the standard 5 cm below surface measurement depth and probes at 2, 10 and integrated 0–5.7 cm depths installed within the same study plot. Overall this study demonstrates that the Hydra Probe offers promise for near surface soil F/T detection using existing soil moisture monitoring networks particularly for the fall freeze.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| 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 it