Time series of bio‐optical properties in a subtropical gyre: Implications for the evaluation of interannual trends of biogeochemical properties
Bibliographic record
Abstract
With a validated Quasi‐Analytical Algorithm, an 11 year (1998–2008) monthly time series of the primary optical properties of waters in the center of the South Pacific gyre was developed from Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Also derived are chlorophyll a (Chl a) concentrations with the operational empirical algorithms for SeaWiFS and MODIS. The optical properties include the absorption coefficient (at 443 nm) of phytoplankton (aph) and that of the combination of detritus and gelbstoff (adg). From these time series, we further derived their annual background (summer low) and seasonal intensity (the difference between winter high and summer low). These time series show that (1) the optical properties have different seasonal and interannual variations, indicating different dynamics of these properties in the subtropical gyre; (2) there is a decreasing trend (r2 = 0.24) of the background aph in the 1998–2008 period and an increasing trend of the aph seasonal intensity (r2 = 0.11) for this period, and both trends are not statistically significant; (3) the aph time series agrees with the Chl a time series at the seasonal scale, but differs with respect to interannual variations; and (4) different interannual trends could be inferred with different time frames. These results emphasize that it is difficult to draw unequivocal conclusions about long‐term trends of biogeochemical properties in the oceans with the current relatively short bio‐optical records. To clarify and predict such trends, it is critical to get a full account of the forces that are responsible for the seasonal and interannual variations of these properties.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".