Clayoquot Sound Harmful Algal Blooms Investigation of Tofino Inlet - 2019
Bibliographic record
Abstract
The University of Washington Tacoma has conducted yearly summer research expeditions to Clayoquot Sound along the west coast of Vancouver Island, British Columbia since in 2000. Data collected in the region examined the changing conditions in water properties at 86 different sites in Clayoquot Sound every summer. This research focused on the data collected from Tofino Inlet in 2019 and was compared to the Tofino Inlet data from 2014. Data was analyzed using GIS maps of nutrient distribution and contour profile plots to determine if rising temperatures from "the Blob", a warm water anomaly, created more favorable conditions for harmful algal blooms. The 2014 data had some stations with higher surface nutrients than 2019, while 2019 had some stations with higher bottom nutrients when compared to 2014. There was also an overall pattern in Tofino Inlet of warmer temperatures in 2019 than in 2014.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".