Database of the Operational Drifter Observations in the Arctic Region
Bibliographic record
Abstract
The database (formed in MHI) for 22 drifters deployed in the Arctic region in 2012 -2016 is represented.The most intensive drifter observations were performed in the Beaufort Sea (the Canada Basin) and in the Central Arctic.According to the data of temperature-profiling drifters, ~ 2 million temperature profiles (including the ones acquired under the ice formations) and ~ 120.000 atmospheric pressure measurements were obtained.Total life time of drifters as at August 2016 exceeded 7000 days.General information and technical characteristics of BTC60/GPS/ice/1ps, BTC60/GPS/ice/3ps, SVP-BTC80/GPS temperatureprofiling drifters are given.Features of drifter information primary preparation are enumerated and the technique of database quality assessment is shown.The studies have shown that temperature-profiling data provides the assessment of the ice thickness and its spatial-temporal variability in the region.The results of the experiments carried out in the Arctic reveal the fact that autonomous temperature-profiling "ice" drifters are an effective instrument for studying the Arctic region.According to the results of the experiments carried out in the Arctic and verification of data quality in the formed database, the drifters showed the reliability of operational characteristics.This is confirmed by failure-free operation of IMEI 245950/WMO 48541 drifter which had been performed the measurements during 1.083 days.The obtained unique long-term series of systematic operational data can be applied for clarifying the concepts of thermal processes variability in the upper ocean layer (including the under-ice one), the dynamics of ice fields and air pressure fields in a wide range of spatial-temporal scales as well as for refining the concept of interaction processes in the Atmosphere -Ice -Ocean system.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".