CS725, An Accurate Sensor for the Snow Water Equivalent and Soil Moisture Measurements
Bibliographic record
Abstract
The CS725 is manufactured by Campbell Scientific (Canada) Corp - CSC and patented by Hydro-Quebec. The CS725 is designed to determine four times a day the snow water equivalent (SWE) up to 600 mm and soil moisture by measuring the natural ground gamma radiation over an ar- ea of more than 100 m 2 . The performances of the CS725 sensor are highlighted according to the re- s ults collected over more than 5 years by Hydro-Quebec. The manual SWE reference data are mainly collected from the snow pit method. The snow core technique is also used, but has more drawbacks to produce reliable data under icy snow conditions. The CS725 delivers accurate SWE data regardless of soil type (inorganic or organic) through a calibration method that we have developed. We have learned that a long enough off-snow period must be investigated in order to set properly the CS725's parameters. We have also found that the soil moisture does not vary significantly during the winter season and it is considered constant thereby simplifying the mathematical equations. From all our in- vestigations, we have proved that CS725 is able to quantify the SWE of a snowpack at an accuracy level of 5±%.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.010 | 0.003 |
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".