The Variability of the Size Distributions of Submicron Particles in the Oceans
Bibliographic record
Abstract
Abstract The size distribution of submicron particles is essential for understanding their biogeochemical and optical roles, but it has seldom been measured. This study utilizes ViewSizer 3000, an instrument that tracks Brownian motions of particles, to measure the particle size distributions (PSD) from 250 to 1,050 nm in the North Pacific Ocean (NP) and the North Atlantic Ocean (NA) at depths from 5 to 500 m. The concentration of particles varies over one order of magnitude at any given size bin, with greater variations up to two orders of magnitude at sizes >600 nm. In both locations, concentrations decrease with depth. Bacterioplankton are a dominant component, accounting for 65%–90% of the submicron particles in the surface waters (<100 m) and approximately 30%–40% at depths >150 m at both sites. In the NP, the volume mean diameter increased approximately 5% from the morning to noon at the surface, probably resulting from the diurnal growth of bacterioplankton. In the NA, the concentration and mean size increased by >60% and ∼10% respectively after one storm that introduced a different particle population into the study area.
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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 | 0.001 | 0.001 |
| 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".