Carbonate Chemistry Along a Small River-Coastal Ocean Continuum (Kamouraska River, Qc, Canada)
Bibliographic record
Abstract
This dataset contains all the chemical parameters measured during expeditions between May and October 2022 in the surface waters of Kamouraska's coastal waters. The data are divided into two databases. The first contains all chemical parameters measured at fixed stations. Sampling was carried out along the Kamouraska River - Upper St. Lawrence Estuary coastal water continuum at 10 to 13 stations, depending on the expedition. The sampling strategy was to start collecting samples in the Kamouraska River at high-water slack water, then move towards the upper St. Lawrence estuary. Fixed stations upstream of the Kamouraska River, where the water is too low to go up with the boat, and at the mouth of the Kamouraska River, are also included in this database, along with the coordinates of all the stations. Surface water samples were collected using a Niskin bottle, and physico-chemical parameters were obtained using a CTD probe on board the boat, and using a YSI probe for the other stations. Parameters measured include : Temperature - T pHNBS pHT Practical salinity Dissolved inorganic carbon - DIC Measured Total alkalinity - TAmeas Calculated Total alkalinity - TAcalc 13C signature of the DIC - δC13-DIC Total nitrates - ƩNO3 Nitrites – NO2- Soluble reactive phosphorus – SRP Dissolved silicate - DSi The second database contains in situ data collected in parallel. Continuous pCO2 measurements were taken from the boat. A submersible pump was deployed from the side of the boat, pumping surface water into a degassing chamber connected to a CO2 analyzer (LI-830). Data are obtained every second, 5 seconds or 30 seconds depending on the expedition, and each measurement is coupled to a GPS position.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".