Toward a quantitative and empirical dissolved organic carbon budget for the Gulf of Maine, a semienclosed shelf sea
Bibliographic record
Abstract
Abstract A time series of organic carbon export from Gulf of Maine (GoM) watersheds was compared to a time series of biological, chemical, bio‐optical, and hydrographic properties, measured across the GoM between Yarmouth, NS, Canada, and Portland, ME, U.S. Optical proxies were used to quantify the dissolved organic carbon (DOC) and particulate organic carbon in the GoM. The Load Estimator regression model applied to river discharge data demonstrated that riverine DOC export (and its decadal variance) has increased over the last 80 years. Several extraordinarily wet years (2006–2010) resulted in a massive pulse of chromophoric dissolved organic matter (CDOM; proxy for DOC) into the western GoM along with unidentified optically scattering material (<0.2 µm diameter). A survey of DOC in the GoM and Scotian Shelf showed the strong influence of the Gulf of Saint Lawrence on the DOC that enters the GoM. A deep plume of CDOM‐rich water was observed near the coast of Maine which decreased in concentration eastward. The Forel‐Ule color scale was derived and compared to the same measurements made in 1912–1913 by Henry Bigelow. Results show that the GoM has yellowed in the last century, particularly in the region of the extension of the Eastern Maine Coastal Current. Time lags between DOC discharge and its appearance in the GoM increased with distance from the river mouths. Algae were also a significant source of DOC but not CDOM. Gulf‐wide algal primary production has decreased. Increases in precipitation and DOC discharge to the GoM are predicted over the next century.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".