Plankton are not passive tracers: Plankton in a turbulent environment
Bibliographic record
Abstract
Spectral analysis was performed on a series of oceanographic transects collected using an optical plankton counter and conductivity‐temperature‐depth probe. The “physical” time series (i.e., temperature) power spectra showed a single passive scaling relationship across the entire range of sampling scales (1–8192 s) that was expected from turbulence. However, the “biological” time series possessed more than one scaling region. The Chl a fluorescence had three scaling regions, a flattened (whitened) intermediate range bound by passive regions at scales approximately <30 and >300 s. Cross‐spectral analysis indicated that the chlorophyll‐temperature spectra were similar at these scales. The zooplankton biomass had a single break in the power spectrum and was passive only at scales >300 s, the zooplankton‐temperature spectra being similar only at these scales. The zooplankton‐chlorophyll cross‐spectra were often negatively coupled at the intermediate (300–30 s) scale giving a strong indication that zooplankton grazing was affecting the phytoplankton distributions.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".