Bibliographic record
Abstract
Nitinat Lake is a long, narrow, and strongly salt-stratified fjord-lake located on the west coast of Vancouver Island, British Columbia. It is connected to the ocean by a 3km long natural channel, only 2.5m deep at low normal tides that limits exchange between the 203m deep lake and the Pacific Ocean. Lake-water may be grouped into two distinct bodies: a weakly stratified bottom layer containing seawater, and a strongly stratified surface layer containing brackish water. The permanently anoxic bottom layer has high concentrations of hydrogen sulphide and a long residence time. At rest, the interface between these two bodies of water ranges from 5m to 15m in depth depending upon location and season. Surface layer salinity was found to correlated well with precipitation in the watershed. The lake contains several large salmon runs and is home to the largest salmon hatchery in Canada, rearing over 40 million fry annually. Upwelling events of anoxic water are potentially catastrophic for fish hatchery operations such as fish harvesting and juvenile releases, highlighting the need to better understand the physical mechanisms that lead to upwelling. Meteorological, CTD, and thermistor chain data were used to study wind forcing of the interface. If was found that predictions of interface deflections based upon linear theory of surface stress response for a two-body lake were in reasonable agreement with observed data. However, spatial variations in lake properties appear to be the result of tidal exchanges between the lake and the ocean, with anoxic water commonly found at shallower depths at the inland end of the lake than the ocean end. This spatial variation of properties adversely affects linear theory predictions, and further understanding of tidal exchanges and internal lake dynamics are required in order to better predict upwelling of anoxic water at this time.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".