The statistical correlations of rate of change of TEC index (ROTI) on the standard scintillation indices over the Canadian Arctic
Bibliographic record
Abstract
For decades, the Rate of Change of Total Electron Content Index (ROTI) has been employed to monitor and quantify ionospheric irregularities, serving as a potential substitute for standard scintillation indices. However, to date, ROTI has not been sufficiently investigated in terms of its relationship with standard scintillation indices. This study presents a preliminarily statistical analysis of the relationship between ROTI and standard scintillation indices using GPS receivers from the Canadian High Arctic Ionospheric Network (CHAIN) over a 5-year period from 2011 to 2015. Our results show that as ROTI increases, the phase scintillation index (σφ) exhibits a corresponding linear increase (slope of ∼0.34), while the amplitude scintillation index (S4) shows little to no enhancement (slope of ∼0.05). Both relationships exhibit high correlation, with coefficients of approximately 0.93 and 0.82, respectively. The differentiated responses suggest that the significant enhancement of standard phase scintillation index is fundamentally dominated by refractive effects, which is primarily driven by large-scale ionospheric structures (>Fresnel-scale probably). The feeble inflation of S4 supports the assertion. Accordingly, the linear relationship solely between ROTI and σφ suggests that the increase in ROTI can be used to empirically assess the contribution of refractive variations to the enhancement of σφ at high latitudes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".