Time-Series Modeling of Data on Coastline Advance and Retreat
Bibliographic record
Abstract
An empirical time series (1941–2007) of advance and retreat data from the coast of Guyana is modeled with statistical time-series techniques. Subseries of 5-y periods are fitted to modified Box-Jenkins space–time models. Second-order spatial-cyclic autoregressive models, associated with cyclical advance and retreat patterns, fit the data for five different subseries. First-order autoregressive models are also suitable to describe the data from five other subseries, thereby suggesting a long-memory response in the coastal system. Three of the subseries are fitted to space–time autoregressive moving-average models, thereby indicating the presence of random shocks (i.e., random events) in the coastal system. The various models are indicative of cyclical, long-memory, and short-memory processes operating in the coastal system. These processes can be associated with mudshoal propagation and stabilization and with temporal stochastic processes that force the coast to advance or retreat in different locations.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".