Zooplankton and micronekton vertical distribution and diel vertical migration behaviour in the Northern North Atlantic Ocean
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.During the Norwegian Trans-Atlantic cruise covering the central parts of four north Atlantic ocean basins, the Norwegian Sea (NS), Iceland Sea (ICS), Irminger Sea (IRS), and Labrador Sea (LS), data on vertical distributions of mesozooplankton to micronekton components were collected using a combination of hull-mounted and towed multi-frequency acoustics, OPC (Optical Particle Counter), and VPR (Video Plankton Recorder). In addition, data on both surface light, as well as the light regimes in different hydrographical regions were collected. Daytime depths of mesopelagic scattering layers showed strong correlation with optical conditions, with shallow daytime distributions occurring in regions with low light penetration, and deeper daytime distributions in regions with clearer waters. For micronekton, DVM behaviour in the eastern basins (NS and ICS) was heavily influenced by the short summer nights, with duration of nocturnal descent coinciding with night lengths, and depths reached during nighttime depending on latitude. Mesozooplankton showed less pronounced migrations and were generally more shallowly distributed during the day. Recent works have suggested a strong dependence of daytime depths of vertical migrators on oxygen conditions, but in the highly oxygenated North Atlantic light conditions at depth appear to exert a strong control on their vertical distribution. Since factors controlling vertical distribution and migratory behaviour may affect predator-prey relationships through vertical overlap, we explore vertical overlap between mesozooplankton prey and micronekton predators under different optical regimes during the 2013 Norwegian Euro-BASIN cruise.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".