Darnley Bay nearshore fish survey : synthesis of 2012 and 2014–2016 field programs
Bibliographic record
Abstract
Sampling of coastal fishes was conducted in Darnley Bay in the summer of 2012, and in 2014 to 2016 in order to establish baseline information of the community composition of nearshore fishes and identify their habitat associations within the Anguniaqvia Niqiqyuam Marine Protected Area. Surveys were conducted at three remote field locations (Bennett Point, 69°72’84” N, 124°08’90” W; Brown’s Harbour, 70°12’05” N, 124°38’95” W; and Argo Bay, 69⁰23’37” N, 124⁰27’48” W) where fishes were collected and processed for basic biological data (i.e., length, weight, and age). The results of species collected, their biological information and environmental characteristics at their location of capture (i.e., depth, salinity and temperature) are presented in this report. Overall 18 species were identified among surveys, in which species diversity and abundance was greatest in Argo Bay (16 species; total fish captured n=1315). Species composition varied, such that depending on the year either Saffron Cod (Eleginus gracilis (Tilesius, 1810)), Capelin (Mallotus villosus, Müller, 1776) or Shorthorn Sculplin (Myoxocephalus scorpius, Linnaeus, 1758) were most abundant in 2012, 2014 and 2015 respectively, or by location where juvenile Broad Whitefish were most abundant (Coregonus nasus, Pallas 1776) in Argo Bay in 2016. Generally, the southern-most region of Darnley Bay (Argo Bay) was warmer and less saline than the northern sites (Bennett Point and Brown’s Harbour) on the Cape Parry peninsula.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".