DFO Pacific Groundfish Synoptic Trawl Surveys - Strait of Georgia
Bibliographic record
Abstract
The Strait of Georgia (SOG) synoptic bottom trawl survey was conducted in 2012 and 2015. This survey is one of a set of long-term and coordinated surveys that together cover the continental shelf and upper slope of most of the British Columbia coast. The other surveys are the Queen Charlotte Sound (QCS) survey, the Hecate Strait (HS) survey, the West Coast Vancouver Island (WCVI) survey and the West Coast Haida Gwaii (WCHG) survey. The objectives of these surveys are to provide fishery independent abundance indices of all demersal fish species available to bottom trawling and to collect biological samples of selected species. The surveys follow a random depth-stratified design and the sampling units are 2 km by 2 km blocks.The synoptic bottom trawl surveys are conducted by Fisheries and Oceans Canada (DFO) in collaboration with the Canadian Groundfish Research and Conservation Society (CGRCS), a non-profit society composed of participants in the British Columbia commercial groundfish trawl fishery. The Queen Charlotte Sound and West Coast Haida Gwaii surveys are conducted under collaborative agreements, with the CGRCS providing chartered commercial fishing vessels and field technicians, while DFO provides in-kind contributions for running the surveys including personnel and equipment. The Hecate Strait, West Coast Vancouver Island, and Strait of Georgia surveys are conducted by DFO and have typically taken place on the Canadian Coast Guard research vessel W.E. Ricker. In years when the W.E. Ricker has not been available, the Hecate Strait and West Coast Vancouver Island surveys have taken place on chartered industry vessels. Data from these surveys are also presented in the groundfish data synopsis report (Anderson et al. 2019).The data provided include information about the annual survey trips and fishing events (tows/sets) that are part of this survey series, including the vessel name, dates, times, spatial coverage, gear details, and effort information. Catch information (total weight in kg or counts of individual specimens) is included from successful fishing events. Catches are identified to species or to the lowest taxonomic level possible. Most catches are weighed, but some are too small (“trace” amounts) or too large (e.g. very large Big Skate). Some catches were subsampled and biological data were collected from individual fish specimens, including length, sex, and weight information. Where age structures were collected and processed, fish ages have been included. Relative abundance indices are provided for species that have been captured in every survey of the time series. The coefficient of variation and bootstrapped 95% confidence intervals are provided for each index. The groundfish data synopsis report (Anderson et al. 2019) provides an explanation of how the relative biomass indices are derived.
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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) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".