Assessing permafrost erosion in the Canadian Beaufort Sea, Herschel Island - a biomarker approach
Bibliographic record
Abstract
Herschel Island is the remnant of an ice-push moraine, formed during the farthest advance of the Laurentide Ice Sheet in the late Wisconsin. The island is located in the Canadian Beaufort Sea, in the northwestern part of the Yukon Territory. A marine depression (Herschel Basin), southeastern adjacent to Herschel Island, acts as a sink of organic matter (OM) derived from various sources.The main objective of this master thesis was to determine the amount of OM, derived from Herschel Island, in the deposits of Herschel Basin. Rapidly increasing mean annual air temperatures (MAAT) in high latitude areas raise awareness of a changing Arctic climate and consequences for the Arctic carbon cycle. Biomarker analyses of soil and sediment samples from various study sites on and around Herschel Island show that sediments in Herschel Basin are of prevailing terrigenous origin. Approximately 60 % of the OM in the surface sediments of Herschel Basin and the adjacent nearshore area can be assigned to eroded material from Herschel Island. Investigations on a sediment core from the centre of the basin suggest enhanced erosion rates and increased supply by OM from Herschel Island in the upper section of the core. Results of biomarker analyses of this thesis corroborate a progressing change of the Arctic climate, amplified by positive carbon feedback mechanisms.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".