2022William-Kennedy expedition: Nunatsiavut Coastal Interaction Project (NCIP)
Bibliographic record
Abstract
The accelerating Arctic cryosphere decline severely impacts the land on which northern communities live through the presence of coastal and marine geohazards and coastal erosion, which further places the cultural heritage of coastal archaeological sites at risks. Sea ice decline also compromises the formation of polynyas, with unknown consequences for the regional ecosystems. From the 10th to the 18th of July 2022, a scientific cruise onboard the research vessel William-Kennedy allowed the collection of a suite of samples and data from the marine coastal environment of Nain, Nunatsiavut. In total, 42 surface sediment samples, 29 sediment cores, 41 conductivity-temperature-depth (CTD) profiles, 13 water samples, 24 phytoplankton nets and 13 zooplankton nets were collected. The cruise allowed the deployment of 2 moorings equipped with sediment traps in Nain Bay and within deeper offshore waters. Triangulation showed that the 2 moorings were correctly placed near their target locations. Drop camera transects were deployed in Webb Bay and at the easternmost tip of Paulmp;gt;'s Island to image the seabed and study benthic habitats. Finally, acoustic sub-bottom profiling along the entire study area allowed a high-resolution characterization of the stratigraphy of the seafloor, helped identifying locations for sediment sampling and inferring geological information about the depositional environments. The material and data collected during the research cruise will be key to 1) evaluating the productivity and dynamics of small recurring polynyas (i.e., rattles) on diverse timescales, 2) assessing marine and coastal geohazards (e.g., landslides) in relation to the deglacial history of Nain, 3) investigate the seabed geomorphology in Webb Bay and linkages with permafrost and sea-level changes and 3) conducting benthic habitat characterization. Co-led by the University of New Brunswick (UNB) and Natural Resources Canada (NRCan), this cruise was done in collaboration with the Government of Nunatsiavut, Université du Québec à Montréal, Université Laval, Dalhousie University and Memorial University, and was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) and NRCan.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.075 | 0.012 |
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".