Marine debris on the coast of Southwest Nova Scotia : an analysis
Bibliographic record
Abstract
This thesis analyzes the levels of marine debris on the coastline of Southwest Nova Scotia and draws possible conclusions for the observed degree of pollution.The plentiful stocks of lobster, scallop, herring, and other marine life in the Atlantic waters surrounding Nova Scotia have led to the creation of multiple commercial fisheries in the Atlantic Canadian region; in addition to the Indigenous fishery that has existed predating Canadian federation.This research sought to identify explanatory variables that could be used to explain the variances in debris levels at different beach sites.It was found that factors relating to the commercial fishing industry may not be as relevant to determining the debris levels as one may think.Date: April 7, 2021 Without the help of multiple individuals, it would not have been possible to complete this research.I would like to start by thanking my supervisor Dr. Mark Raymond, for his support and advice throughout my academic career at Saint Mary's University, and for his belief in this project.Without his guidance and knowledge, I would not have been able to develop this research from the data collection, to the submission of this thesis.I would also like to thank Joshua Watkins & James Blair for the many hours they accompanied me at the data collection sites, and standing in the cold and wind as the counts were conducted.Without their help, the data collection would have been much more difficult.I also give thanks to Dr. Yigit Aydede for his constant support throughout the time that I have known him at Saint Mary's, and for always being willing to lend a hand whenever I needed him.It is because of his excellent teaching, that I was prepared to author this thesis.Finally, I want to give thanks to my parents.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".