A top to bottom evaluation of IRI 2007 within the polar cap
Bibliographic record
Abstract
Abstract Monthly median values of ionospheric peak height (hmF2) and density (NmF2), derived from ionosonde measurements at four Canadian High Arctic Ionospheric Network (CHAIN) stations situated within the polar cap and Auroral Oval, are used to evaluate the performance of the International Reference Ionosphere (IRI) 2007 empirical ionospheric model during the recent solar minimum between 2008 and 2010. This analysis demonstrates notable differences between IRI and ionosonde NmF2 diurnal and seasonal behavior over the entire period studied, where good agreement is found during summer periods but otherwise errors in excess of 50% were prevalent, particularly during equinox periods. hmF2 is found to be marginally overestimated during winter and equinox nighttime, while also being underestimated during summer and equinox daytime by in excess of 25%. These errors are shown to be related to significant mismodeling of the M(3000)F2 propagation factor. The ionospheric bottomside thickness parameter (B0) is also evaluated using ionosonde measurements. It is found that both of the IRI's internal B0 models significantly misrepresent both seasonal and diurnal variations in bottomside thickness when compared to ionosonde observations, where errors at times exceed 40%. A comparison is also presented between IRI and Resolute (74.75N, 265.00E) Advanced Modular Incoherent Scatter Radar (AMISR)‐derived topside thickness. It is found in this comparison that the IRI is capable of modeling ionospheric topside thickness exceptionally well during winter and summer periods but fails to represent significant diurnal variability during the equinoxes and seasonal variations.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".