DFO Quebec Region Ecosystemic bottom trawl surveys 2004-2022
Bibliographic record
Abstract
Fisheries and Oceans Canada Quebec Region (DFO-Qc) conducts a multidisciplinary scientific bottom trawl survey in the estuary and northern Gulf of St. Lawrence (NAFO areas 4RST) every year since 1978. Survey data are collected following a stratified random sampling with a bottom trawl. The main objectives are to examine spatial and temporal changes in the distribution and relative abundance of fish and their assemblages and biological parameters of commercial species. Over the years, this survey has been conducted aboard five vessels: the MV Gadus Atlantica (1978-1994), the MV Lady Hammond (1984-1990), the CCGS Alfred Needler (1990-2005), the CCGS Teleost ( 2004-2022) and since 2022 the CCGS John Cabot. The objectives, the protocols, the identification of species as well as the trawl used during the various surveys changed over time. The data are therefore not directly comparable between these surveys. Comparative analyzes were carried between vessels and conversion factors are available for a number of species. Contact the team for more information. This data constitutes an OBIS version of the data collected from 2004 to 2021 onboard the CCGS Teleost. At each sampling station, a Campelen 1800 shrimp trawl with a 12.7 mm mesh lining in the codend is towed for 15 minutes on the bottom at each sampling station. Physical oceanographic data are also collected at most stations using CTDs attached to the back of the trawl, a rosette and a zooplankton net. The OBIS view of this dataset includes presence and biomass information for fish and invertebrates species at the survey station locations. Data collected onboard the CCGS Alfred Needler (1990-2005) are also available on Obis.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.375 |
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; both teacher heads agree on what is shown here.
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".