River‐tide dynamics: Exploration of nonstationary and nonlinear tidal behavior in the <scp>Y</scp>angtze <scp>R</scp>iver estuary
Why this work is in the frame
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Bibliographic record
Abstract
Abstract River‐tide dynamics remain poorly understood, in part because conventional harmonic analysis (HA) does not cope effectively with nonstationary signals. To explore nonstationary behavior of river tides and the modulation effects of river discharge, this work analyzes tidal signals in the Yangtze River estuary using both HA in a nonstationary mode and continuous wavelet transforms (CWT). The Yangtze is an excellent natural laboratory to analyze river tides because of its high and variable flow, its length, and the fact that there are do dams or reflecting barriers within the tidal part of the system. Analysis of tidal frequencies by CWT and analysis of subtidal water level and tidal ranges reveal a broad range of subtidal variations over fortnightly, monthly, semiannual, and annual frequencies driven by subtidal variations in friction and by variable river discharges. We employ HA in a nonstationary mode (NSHA) by segregating data within defined flow ranges into separate analyses. NSHA quantifies the decay of the principal tides and the modulation of M 4 tide with increasing river discharges. M 4 amplitudes decrease far upriver (landward portion of the estuary) and conversely increase close to the ocean as river discharge increases. The fortnightly frequencies reach an amplitude maximum upriver of that for over tide frequencies, due to the longer wavelength of the fortnightly constituents. These methods and findings should be applicable to large tidal rivers globally and have broad implications regarding management of navigation channels and ecosystems in tidal rivers.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it