CTD profiles in the bay of Sept-Îles in 2017/2018
Bibliographic record
Abstract
This data set contains temperature, salinity, oxygen, fluorescence, turbidity, and currents data collected in the bay of Sept-îles, on the north shore of the Gulf of St. Lawrence, Canada. Five sampling campaigns were conducted from May to September of 2017, to assess seasonal variations in the oceanographic conditions. An additional campaign was conducted in May 2018, focusing on the measurement of currents. These surveys covered the inside of the bay and the nearby archipelago. The bay of Sept-Îles has recently been the subject of a multidisciplinary study by the Canadian Healthy Oceans Network (CHONe II) because it is a heavily industrialized and urban coastal area at Canadian midlatitudes. It is therefore a good site to study the impact of such human presence on adjacent marine ecosystems. The objective of this data set was to enable the development and calibration of hydrodynamic and biogeochemical models of the bay, which was hindered by scarce knowledge of the environmental conditions. Water properties were collected using a Seabird Electronics SBE19plus and a Sontek CastAway CTD probe. Currents were measured using a towed acoustic Doppler current profiler (ADCP) model Teledyne RDI Sentinel V, and passive surface drifters which used Spot GPS probes.
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 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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".