TERIFIC 2nd Ocean Glider Deployments in the Labrador Sea
Bibliographic record
Abstract
As part of the TERIFIC (Targeted Experiment to Reconcile Increased Freshwater with Increased Convection) project funded by the European Research Council, two G2 Slocum gliders (398 and 409) from Teledyne Webb Research were deployed offshore of Qaqortoq, southwest of Greenland, in December 2021 from the 30-m research vessel Adolf Jensen. Both gliders were retrieved in late May 2022 onboard the RV Celtic Explorer southwest of the Labrador Sea. Pumped Slocum Glider Payload CTDs (Conductivity, Temperature, and Depth) provided by Sea-Bird Electronics (Bellevue, WA) were mounted on both Slocum with a sampling frequency of 0.5 Hz. An Aanderaa oxygen optode was also fixed on both gliders, with the optode on glider 409 fitted in an outside bracket. Both gliders were equipped with WETLabs (Western Environmental Technologies Laboratories) ECO Puck that measures chlorophyll and optical backscatter (532 and 700 nm) for 398 (BB2FLSLC) and chlorophyll, colored dissolved organic matter and optical backscatter (700 nm) for 409 (FLBBCDSLC). Initial processing was done with the toolbox PyGlider and both gliders were processed with the GliderTools toolbox (Gregor et al., 2019) to determine qc temperature and salinity variables. The vertical water velocity is estimated with the GliderFlight toolbox using a steady-state flight model.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".