CTD Data for the 2024 BioDiv Spring Cruise in the Saint-Lawrence Gulf
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.015 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it