TERIFIC project, 26 November – 10 December 2019
Bibliographic record
Abstract
The purpose of the fieldwork activities detailed in this report was to deploy a range of autonomous platforms to measure physical oceanographic properties at the west Greenland margin and Labrador Sea. The land-based fieldwork spanned the dates in this report, while the seagoing activities were accomplished with 1 day of work onboard the Adolf Jensen, a 30m Greenlandic vessel. \n \nThe autonomous platforms used included: two Seagliders (sg602 and sg638) equipped with CTDs, oxygen and biooptics (WETlabs triple puck); an autonomous surface vehicle (Sailbuoy Artemis) measuring surface temperature and salinity, surface wind speed and direction and air temperature, and a wave sensor; 50 standard Global Drifter Program drifters measuring temperature and their position; and 3 drifters measuring surface temperature and salinity sensors and barometric pressure. The drifters were deployed at the continental shelf edge offshore of Qaqortoq, Greenland on December 4. The gliders and autonomous surface vehicle were deployed on the shelf and transited offshore to the central Labrador Sea.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.389 | 0.314 |
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".