Tidal Currents in Douglas Channel, British Columbia: Evaluation and Prediction
Bibliographic record
Abstract
Douglas Channel is the principal shipping route between the town of Kitimat and the Pacific Ocean. Prediction of near-surface currents is crucial for safe tanker navigation and cleaning-up oil spills. Three years of current velocity data were collected at two moorings located 30 km apart. Spectral, wavelet, and harmonic analysis of measured currents throughout the upper (40-m) and lower (50–358 m) water columns indicated the predominant influence of semidiurnal (SD) tidal currents. In the upper layer, wind and density flows resulted in considerable seasonal and interannual variability of these currents. Analysis of the SD variance reveals three major components: barotropic, coherent baroclinic, and random baroclinic. The predictability of near-surface currents depends on the relative contribution and stability of the first two components. Tidal constants estimated for one year were used to predict currents for two other years; we found that at the mooring closer to the entrance of Douglas Channel, 80 to 89% of the SD energy in the upper layer and 89–93% in the lower layer can be forecasted, while closer to the two channel head, these numbers are smaller: 55–70% and 79–89%, respectively.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".