Temporal trend analysis of synthetic and real hydroclimate time series and impacts of long term quasi-periodic components on trend tests
Bibliographic record
Abstract
Studies of climate and hydro-meteorological time series have found the presence of decadal and inter-decadal oscillations of quasi-periodic components (broader band signals) as part of long term natural variations in the data. If the oscillation of the quasi-periodic component is prominent, the impacts on the Mann-Kendall (M-K) and Thiel-Sen (T-S) trend tests could lead to a biased estimate and affect the prediction of future trends. This study performed the Thiel-Sen test on simulated time series of periodic components with and without trends as well as real time series of climate and river discharge data with long records in the Canadian Prairies. The results of tests suggest that the T-S test is sensitive to the presence of oscillation of long term quasi-periodic components. Data record length, magnitude of cyclic components and phase are the three most important factors affecting the M-K type of tests. The conclusion derived for the T-S test in this study can also be applied to the M-K test.
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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 | 0.009 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".