Baseline benthic plastic debris assessment and intertidal survey in Iqaluit, Nunavut Canada for 2016 and 2017
Bibliographic record
Abstract
Marine plastic pollution is a global issue affecting food webs, humans, and the natural environment. There is limited marine plastic pollution research in Iqaluit and the Arctic in general. This thesis focuses on Iqaluit, Nunavut targeting intertidal and marine benthic debris in areas with high human activity such as fishing and hunting areas, shipping locations, and the proximity to the city. Data includes sampling from October 2017 as well as previously collected (2016) sediment grab samples and seafloor video collection. Benthic grab samples and seafloor video were examined for anthropogenic debris including microplastics (<5mm) and macroplastics (>5mm). An intertidal survey was conducted at low tide to determine the amount and types of land-derived plastic debris that may enter Frobisher Bay as a possible point source for marine plastic pollution. Determining the abundance of both microplastics and macroplastics will create a baseline for marine plastic pollution found in Frobisher Bay, NU. This thesis includes protocols for sampling in extreme environments and provides an analysis of methods that are replicable for monitoring benthic and terrestrial marine debris. No significant changes in benthic marine debris occurred during 2016 and 2017. The results indicate a baseline of 0.002 plastics/mL of benthic debris, 0.055 plastics/minute for benthic seafloor video, and 0.379 plastics/m2 of shoreline debris for marine debris in the Frobisher Bay area and Iqaluit, Nunavut.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".