Timing, progression, duration: an investigation of temporal patterns of break-up and ice jam flooding in the Mackenzie Delta, NWT
Bibliographic record
Abstract
The Mackenzie Delta is covered in freshwater lakes that provide habitat for a myriad of species. The hydrology of these delta lakes is dominated by cryospheric processes, specifically snowmelt induced spring break-up ice jams, which typically produce the largest hydrologic event of the year. In light of limited current understanding of break-up patterns and processes in the delta, the objective of this research is to explore the temporal variability of break-up and ice-affected extreme floods in the delta. Data gathered from a variety of sources, including hydrometric and meteorological stations, radar and satellite imagery, air photography, and historical observations, are assembled to create a break-up chronology for the delta. This includes an index of the timing of initiation of pronounced spring melting, as well as the initiation of break-up, the peak break-up water level, and the last day of ice effects for 15 Water Survey of Canada hydrometric stations in the Mackenzie Delta over the period from 1972 to 2006. Within the subset of identified extreme flood years, distinct timing patterns emerge, which can ultimately be linked to dominant hydroclimatic influences. These findings are part of the first stage of an ongoing investigation into the hydroclimatic controls on extreme hydrological events in the Mackenzie Delta.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".