Hourly lake level data across the Peace-Athabasca Delta (Canada) in 2018 and 2019
Bibliographic record
Abstract
This is the dataset associated with the publication “A new lake classification scheme for the Peace-Athabasca Delta (Canada) characterizes hydrological processes that cause lake-level variation” published in Journal of Hydrology: Regional Studies (2021). Included are three data files: hourly lake level measurements at 48 sites in 2018 hourly lake level measurements at 53 sites in 2019 geographical coordinates for these sites, all located within the Peace-Athabasca Delta in northeastern Alberta, Canada Raw data collected using HOBO Water Level Data Loggers were converted from water pressure readings (unit: psi) to water depths (unit: meters) using the Barometric Compensation Assistant in the HOBOware Pro software program. The specified density of water was derived from the temperature channel (assuming freshwater) and a barometric datafile (recorded using a data logger deployed in the field that measured atmospheric temperature and pressure), which was used to convert water pressure readings to water depths. See associated publication for more detailed methods on the deployment of these instruments.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.011 |
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".