RRS James Cook Expedition JC268. ReBELS-1. 15-30 August 2024. (National Oceanography Centre Research Expedition Report, 84).
Bibliographic record
Abstract
The project ReBELS (Resolving Biological carbon Export in the Labrador Sea) is funded by the UK Natural Environmental Research Council (NERC) and aims to understand and quantify the transport of oceanic organic carbon into the deep sea and its effect on ocean carbon storage. To do so, we proposed to set up a year-long ocean observatory in the Labrador Sea using state-of-the-art autonomous observing technologies (gliders and biogeochemical ARGO floats) paired with traditional measurements of carbon flux (moored sediment trap) to understand the different contribution of particle injection pumps to the overall carbon export in the Labrador Sea. This cruise will collect all assets. JC268, is the first of three cruises which set up this year-long observatory in the Labrador Sea. The cruise comprised several goals: - Deploy a mooring, containing 3 sediment traps, physical and bio-optical sensors, acoustic doppler current profilers and current meters and 2 FluxCams (custom-made camera system aiming at characterising the sinking speed of particles). - Deploy 2 BGC-Argo floats, one of them contributing to the BGC-Argo Network and a second one, the ReBELS float, fitted with specialty sensors to characterise particles (UVP6), the upper ocean phytoplankton community (hyperspectral radiometer) and estimate carbon flux (optical sediment trap, transmissometer). - Conduct physical and biogeochemical measurements to validate/calibrate the deployed assets and create a baseline and understanding of the physical and biogeochemical drivers of carbon export. - Conduct opportunistic measurements at the GOSNAP mooring lines around Greenland to validate sensor measurements, in particular oxygen sensors recently fitted on the array. The cruise consisted of 4 main stations: 1. CTD line off Nuuk; 2. mooring; 3. Floats deployment; 4.GOSNAP mooring array.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.301 | 0.143 |
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".