Review of “Impact of land-water sensitivity contrast on MOPITT retrievals and trends over a coastal city” by I. Ashpole and A. Wiacek
Bibliographic record
Abstract
Ashpole and Wiacek analyze a MOPITT CO Level 3 (L3) pixel over one location -Halifax, Canada -and compare it to the Level 2 (L2) retrievals within the same 1 degree pixel.They use this coastal location to highlight instrument sensitivity differences between water and land that impact near-surface and profile analysis with the joint TIR-NIR product.The influence of different surface-types (land or water) on CO retrievals and the resulting trends is investigated.The authors find that sensitivity differences account for retrieval differences in JJA, but a CO gradient is likely the reason for differences in DJF.While the MOPITT team already provide recommendations to maximize information content for a studied region, Ashpole and Wiacek demonstrate the practical implications of retrieval differences.The study suggests L2 profile data over land is C1 AMTD Interactive
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".