Development of a Real-Time Water Quality Buoy for the Fraser River Estuary
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
An innovative project has been initiated to monitor water quality of the Fraser River Estuary as a joint initiative between Environment Canada and the British Columbia Ministry of Environment. Monitoring year-round, real-time, water quality and meteorological parameters in the Fraser River Estuary required a unique approach. Axys Technologies' experience in both the marine, meteorological, and water quality fields was critical to the development of this custom monitoring station. Station location and in-situ water sampling required a moored buoy platform. A Three Meter Oceanographic-Data-Acquisition- System (ODAS) buoy was selected. This platform is capable of surviving freshet conditions in the Fraser Estuary, and support the extensive sampling and monitoring equipment required for this project. The ODAS buoy was modified to include both standard meteorological and multi-parameter water quality sensors, as well as instrumentation needed to collect whole water samples and extract large volumes of water using Solid Phase Extraction (SPE) for the collection of Persistent Organic Pollutant (POP) samples. Monitoring requirements include scheduled continuous and biweekly sampling, along with the ability to distinguish tidally driven events to initiate sampling for organic contaminates. Challenges include the maintenance requirements for each sensor to ensure optimised ongoing operation as well as the vulnerability of this buoy to both vessel traffic and floating debris. Future application development may include automatic data Quality Assurance/Quality Control (QA/QC) and compatibility with a proposed national network.
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.
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 | 0.000 | 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 it