Flow Constraints on Pathways through the Canadian Arctic Archipelago
Bibliographic record
Abstract
To identify flow pathways through the Canadian Arctic Archipelago, numerical model results were examined using two configurations of the Nucleus for European Modelling of the Ocean (NEMO). After correcting for shortwave radiation, the models captured much of the observed spatiotemporal structure of the sea-ice and ocean circulation in the Canadian Arctic Archipelago, especially the southward flow in M'Clintock Channel and the cyclonic circulation in eastern Lancaster Sound. The southward flow in M'Clintock Channel is driven by ageostrophic accelerations and is controlled by topography. Vorticity dynamics analysis showed that both stratification and bathymetry have a strong impact on the circulation in eastern Lancaster Sound. RÉSUMÉ Pour identifier les trajets d’écoulement à travers l'archipel Arctique canadien, nous avons examiné les résultats de modèles numériques en utilisant deux configurations du NEMO (Nucleus for European Modelling of the Ocean). Après avoir appliqué une correction visant à tenir compte du rayonnement de courtes longueurs d'onde, les modèles capturent la majeure partie de la structure spatiotemporelle de la glace de mer et de la circulation océanique dans l'archipel Arctique canadien, en particulier l’écoulement vers le sud dans le détroit de M'Clintock et la circulation cyclonique dans l'est du détroit de Lancaster. L’écoulement vers le sud dans le détroit de M'Clintock est dû à des accélérations agéostrophiques et est contrôlé par la topographie. L'analyse de la dynamique tourbillonnaire a montré que tant la stratification que la bathymétrie ont un effet marqué sur la circulation dans l'est du détroit de Lancaster.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".