Field Collection of Geotechnical Measurements for Remote or Low-Cost Datalogging Requirements
Bibliographic record
Abstract
ABSTRACT Reliable, low-cost datalogging alternatives promote transfer of knowledge and technology to the wider geotechnical and geoscientist community. Alternative systems can ease increased data resolution on large projects, operate in remote locations with restricted site access, or allow developing countries access to reliable and cost-effective datalogging solutions. A low-cost prototype datalogger was developed and tested in the laboratory with the use of open-source materials. Open-source example code is provided at the permanent links included in this paper. The materials for the prototype were 20 % the cost of commercial datalogging units with similar capabilities. With labor, these custom-built units were 35–45 % the cost of a purchased datalogger. Measurements from commercial units and the prototype datalogger were compared to determine the prototype’s accuracy. The datalogger was deployed in place of commercially available dataloggers at three sites across western Canada in the past two years. Laboratory and field testing of the low-cost datalogger has shown the prototype to be easily adaptable to various sensor types. The study experimented with negative pore water pressure (matric suction), volumetric water content, and temperatures from SDI-12 sensors as well as positive pore water pressure and temperature from vibrating wire piezometers. Telemetry modules have been attached to remote dataloggers, transmitting occasional data points, and periodically verifying system operation. Assembly, installation, and monitoring with the low-cost datalogging system over the past two years has demonstrated their durability in field applications. The implementation of a low-cost, open-source geotechnical datalogging system can be a challenge in some locations and requires the consideration of limitations, which are addressed.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".