CICE-Consortium/Icepack: Icepack 1.2.1
Bibliographic record
Abstract
Icepack version 1.2.1 is being released with CICE6.1.1. This is a minor release update from the Icepack1.2.0 release in December, 2019. This release fixes a couple of bugs in the floe size distribution implementation. The ability to run on Mac and Linux computers was added by leveraging conda to install compilers and other supporting software. Documentation was updated as well. Bug fixes: Update to wave fracture including bug fix #299, changes answers for fsd12 cases Update wavespec convergence algorithm to fix bug, reduce memory, and improve performance in the random option implementation, #305 Change order of operations in albedo calculation for restart consistency #303, does not change answers in standard test cases Enhancements: Add adaptive timestepping for FSD lateral melt and growth #298 Update machines/compilers for izumi #295, for cori #304 Add laptop/linux capability via conda #296 Fix nt_zbgc_frac and n_aero initialization in icepack driver #300 #302 Documentation: Add html anchors when reporting results #290 Update community bulletin board/forum links #291 Add information for contributing #293 Update documentation #292, #305 Update copyright and internal version number #301
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.160 | 0.204 |
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".