Correlation of seasonal precipitation isotopic profile with the modern climatological data: a case study from the western Newfoundland region of Canada
Bibliographic record
Abstract
Abstract The measurement of stable water isotopes (i.e. δ 18 O and δ 2 H) in precipitation is a powerful tool for detecting changes in climate patterns, assessing groundwater movements and studying the hydrological budget. In this study, daily precipitation was collected and δ 18 O and δ 2 H were analysed in Corner Brook, western Newfoundland, and Labrador, for 2015. The study provides the first background data of any kind related to liquid water isotopes in western Newfoundland. More than 130 samples were analysed using a state-of-the-art cavity ring-down spectrometer, the Picarro Liquid Water Isotope Analyzer L2130-i, with a minimal instrumental error. The data suggest seasonal variations in which the δ 18 O varies from −33.4 to −0.03‰ (±0.023‰) and δ 2 H ranges from −253.4 to 15.1‰ (±0.148‰). Our data are compared with modern meteorological data and publicly available δ 18 O and δ 2 H data from greater Atlantic Canada, which suggests that the atmospheric circulation patterns, spatial features and other climate factors are distinct in Corner Brook. Isotopes in meteorological precipitation data referenced and collected in this study reflect the cool, wet climate and air-mass fluctuations unique to the geographical region and thus, this baseline is fundamental to understanding the modern isotope hydrological/climatic studies for this region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".