Analyses of Peace River Shallow Water Ice Profiling Sonar data and their implications for the roles played by frazil ice and in situ anchor ice growth in a freezing river
Bibliographic record
Abstract
Abstract. Peace River SWIPS (Shallow Water Ice Profiling Sonar) data were analyzed to quantify the roles of frazil ice and riverbed anchor ice grown in situ during the initial buildup of a seasonal ice cover. Data were derived through quasi-continuous monitoring of frazil parameters throughout the water column, providing direct and indirect measures of anchor ice volume and mass growth rates. Analyses utilized water level and air and water temperature information in conjunction with acoustic volume backscattering coefficient data to track and interpret spatial and temporal changes in riverbed and water column ice. Interest focused on four frazil intervals characterized by anomalously low levels of frazil content (relative to simulations with an anchor-ice-free river ice model) as distinguished by two strikingly different types of time dependences. A simple physical model was proposed to quantitatively account for discrepancies between measured and simulated results in terms of the pronounced dominance of anchor ice as an initial source of river ice volume and mass. The distinctive differences in temporally variable water column frazil content are attributed, in this model, to corresponding differences in the stabilities of riverbed anchor ice layers against detachment and buoyancy-driven movement to the river surface. In accord with earlier observations, the stability of in situ grown riverbed ice layers appears to be inversely proportional to cooling rates. The strength of the coupling between the two studied ice species was shown to be strong enough to detect changes in the anchor ice constituent from variations in water column frazil content.
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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 | 0.000 | 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 | 0.000 |
| 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".