Underway data from estuary transects in Coastal Gulf of Maine (Pleasant, Maine; St. John, New Brunswick) in May and October of 2018 and 2019
Bibliographic record
Abstract
This dataset contains underway data from four organic alkalinity estuary transects, in May and October of 2018 and 2019, completed in the Pleasant (Maine, USA) and St. John (New Brunswick, Canada) estuaries. See "Related Datasets" section for alkalinity data. Discrete samples were collected at intervals of salinity along each estuary. An underway measurements system was also operated during each transect. Discrete samples were analyzed via a number of methods described below. Underway measurements were collected using the procedures described in Hunt et al. (2013). Organic alkalinity is a poorly understood component of the estuarine and coastal ocean acid-base system. This lack of understanding makes assessment of ocean acidification vulnerability and inorganic carbon dynamics more difficult. However, the methods used to quantify organic alkalinity and its effects on the acid-base system are not standardized. In this work we examined several approaches for the measurement of organic alkalinity, and their application to inorganic carbon dynamics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.012 |
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".