Hydrographic and biogeochemical data from Godhäbsfjord and Ameralik Fjord, SW Greenland, 2018-2019
Bibliographic record
Abstract
Dataset containing hydrographic and biogeochemical data from two fjords (Godhäbsfjord and Ameralik Fjord) in southwest Greenland. Data was collected during expeditions in July 2018 (KQ2018) and September 2019 (TU2019), as part of ERC funded (678371) project ICY-LAB (Isotope CYcling in the LABrador Sea) and Royal Society funded (RGF\EA\181036) project Biogeochemical Cycling in Greenlandic Fjords. All data derived from sensors are reported as an average related to the sampling period for the laboratory analysed data. For data corresponding with Towfish samples, this is a time-averaged value, corresponding to the time the Towfish was in the water and sampling occurred. For Niskin derived samples, the average for sensor derived data was calculated from a 5m depth window from a depth profiler CTD. Sampling method refers to the method in water samples were collected, prior to filtration, storage and laboratory analysis. FISH = a Towfish that was deployed for surface (up to 5m, average 3m) sampling. All detailed sampling protocols and station descriptions can be found in the associated cruise reports.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.062 |
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; both teacher heads agree on what is shown here.
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".