Ocean CTD profiles from Jones Sound, Nunavut and adjacent waters collected during the Ice2Ocean Project
Bibliographic record
Abstract
This dataset contains a compilation of conductivity, temperature, and depth (CTD) profiles collected in Jones Sound and surrounding waterways by the collaborative Ice2Ocean project from 2019 onwards. The data were collected to support various research projects investigating the physical oceanography of Jones Sound, northern Baffin Bay, and surrounding waterways, with a focus on understanding changing coastal ocean conditions in the High Arctic, glacier-ocean interactions, and ocean biogeochemistry. Profiles were collected year-round as part of a partnership with the community of Ausuittuq (Grise Fiord) through augered holes in the sea ice at sites accessed by snowmobiles, or from small vessels during the open water season, including numerous local vessels, the polar yacht Vagabond, and the Government of Nunavut research vessel Nuliajuk. Full depth profiles of the water column were obtained along repeat transects by lowering an RBR CTD from the surface to the sea floor using a manual winch. The CTD was outfitted with external sensors for dissolved oxygen, chlorophyll a, turbidity, and photosynthetically-active radiation (PAR) and these fields are included in the dataset. Raw temperature and salinity data were processed in MATLAB by applying a low-pass filter and all fields were binned to 0.5 m depth bins. The external sensors fields have not undergone extensive quality control and require further assessment. Only downcasts are included in the dataset. Water bottle samples were collected at various depths at many of the CTD stations (bottle data is not included here). The CTD data included in this archive is part of an ongoing field program and will be updated annually. For further information on this dataset please contact Andrew K. Hamilton (akhamilton@ualberta.ca)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".