CTD Data for the 2022 COR2212 Cruise in the Saint-Lawrence Estuary
Bibliographic record
Abstract
The objective of mission COR2212 (id: 2022_26) is to monitor natural risks during sediment remobilization and impacts on primary production dynamics in the St. Lawrence Estuary. As part of this mission, vertical CTD (conductivity, temperature, depth) profiles were taken in several areas between Forestville and Pointes-des-Monts (St-Lawrence Estuary). The CTD was also equipped with sensors to measure dissolved oxygen, fluorescence (chl-a), and water clarity in the water column. In addition, surface sediment samples and sediment cores were taken (mainly using a box corer) to determine the sources of the main terrigenous inputs into the estuary, to determine the concentrations of major and trace elements in surface sediments, to document the recurrence of turbidity currents over the last millennium, and to map the distribution of A. catenella in sediments. In addition, samples were taken using a plankton net to determine the abundance and spatial variability of harmful algae (A. catenella). This dataset is part of the EDMS-ISMER-QO collection
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.039 |
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".