Spring 2018 time-series measurement of land-fast sea ice and sub-ice platelet layer thicknesses from electromagnetic induction soundings in McMurdo Sound, Antarctica
Bibliographic record
Abstract
Ground-based electromagnetic induction (EM) time-series measurements of land-fast sea ice and sub-ice platelet layer thicknesses were carried out on land-fast sea ice in McMurdo Sound, Antarctica in winter (August 8 to 26 October) and late spring (November 4-18) of 2018. The EM data were acquired using a frequency-domain Geonics Ltd EM31-MK2 instrument mounted on the sea ice surface in winter and a sledge in late spring. The thicknesses of consolidated ice (sea ice plus the snow layer) and the sub-ice platelet layer were simultaneously retrieved from the EM31 measured response (i.e., Apparent Conductivity (AppCond) and Inphase (Inph)) using the forward modelling and inversion methods of Irvin (2018). Temporal variability in EM measured thicknesses detected the seasonal growth of land-fast sea ice and sub-ice platelet layer in winter, and shorter timescale variability related to strong offshore wind events in winter and the tides in late spring (Brett et al., 2024).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".