Dissolved inorganic carbon (DIC), total alkalinity (TA), water temperature, salinity and dissolved oxygen collected from discrete samples and profile observations during the Canadian Beaufort Sea Marine Ecosystem Assessment (CBS-MEA) F/V Frosti expedition (EXPOCODE 18DN20180803) in the Arctic Ocean, Beaufort Sea from 2018-08-03 to 2018-09-08 (NCEI Accession 0238161)
Bibliographic record
Abstract
This dataset includes discrete sample and profile data collected during the Canadian Beaufort Sea Marine Ecosystem Assessment (CBS-MEA) F/V Frosti expedition (EXPOCODE 18DN20180803) in the Arctic Ocean, Beaufort Sea from 2018-08-03 to 2018-09-08. These data include water temperature, salinity, dissolved oxygen, dissolved inorganic carbon (DIC) and total alkalinity. Starting in 2017, Fisheries and Oceans Canada (DFO) conducted a survey of marine fishes and their habitats on the Canadian Beaufort Shelf and slope in August and early September each year. Sampling was conducted from the F/V Frosti at 144 stations along nine multi-year transects; and 32 non-transect stations. Standardized sampling was conducted at pre-determined depth stations using a variety of sampling equipment including benthic fishing trawls; plankton nets; sediment cores; and CTD and water sample profiles. The ocean acidification program was implemented in DFO’s Central and Arctic Region (Freshwater Institute) in 2017, funded by the Aquatic Climate Change Adaption Services Program (ACCASP). This submission covers measurements conducted in the Canadian Beaufort Sea in 2018.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".