CTD Data for the 2024 BioDiv Spring Cruise in the Saint-Lawrence Gulf
Bibliographic record
Abstract
The aim of the BioDiv (id : 2024_06) mission is to characterize phytoplankton and zooplankton in the coastal zone of the northwestern Gulf of St. Lawrence. As part of this spring mission, CTD (conductivity, temperature, depth) vertical profiles were carried out at 4 sites, each comprising 3 to 4 stations, between Baie-Trinité and Sept-Iles (Quebec North Shore). The CTD was also equipped with sensors to measure dissolved oxygen, turbidity and pH in the water column. In addition, discrete water samples were taken at various stations and depths (surface for all stations, intermediate and bottom when depth is greater than 10m) to provide additional information on the water masses (concentrations of nutrients NO2+NO3, PO4, SiO2, dissolved and total carbon, chlorophyll a and phaeopigment, concentration of phycotoxins, concentration of bacteria, pico- and nanoplankton, flagellates). Phytoplankton were also sampled using a 20µm net and Niskin bottles. Different size classes of zooplankton were collected with 63µm, 200µm and 333 or 500µm nets. This dataset is part of the EDMS-ISMER-QO collection, as well as the Coastal Environmental Baseline Program Initiative under the Oceans Protection Plan of Fisheries and Oceans Canada
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.035 |
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".