CTD sampling in Cambridge Bay, Dease Strait and Queen Maud Gulf, Nunavut
Bibliographic record
Abstract
Conductivity, temperature, as well as other properties at different depths are important characteristics of seawater, with significant effects on the ecology of the ocean in the Arctic. To gain an idea about these seawater properties south of Victoria Island, CTD samplings have been performed from the Martin Bergmann research vessel in the Cambridge Bay, Dease Strait and Queen Maud Gulf by CJ Mundy of the University of Manitoba. Additionally, in order to determine the ideal depth of the CHARS seawater intake pipe, and to meet the required salinity and temperature of the seawater flown into CHARS aquaria, a more targeted CTD sampling has been performed in a section of the east arm of Cambridge Bay offshore of the future CHARS site. This has been accomplished both with a smaller CTD probe launched from a skiff by CHARS staff (data in Ruskin file with extension .rsk, and same data in comma-separated text file, .csv, and Excel spreadsheet, .xls), as well as the larger CTD probe of the 'Martin Bergmann' research vessel by CJ Mundy (data in text files with .int extension).
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".