CICE Consortium/Icepack version 1.1.0
Bibliographic record
Abstract
Icepack version 1.1.0 is being released with CICE version 6.0.0. Among other improvements, this Icepack release adds support for CMIP6 history output, refines the quality control and compliance tests, and extends the test suites with new test configurations. Enhancements: Additional machine support #181 #206 #210 #240 Change statement functions to Fortran standard functions #181 Improved code coverage with extended tests #196 Make automated testing easier #207 Support coupling in RASM #208 #232 Reordered ice_in #210 Improved warning system #212 #234 Move emissivity into namelist #213 Improve initialization for use in CICE #216 Add CMIP6 support #219 Add namelist option to dump restart information at the end of the run #221 Update documentation and license Bug fixes: Ensure that the runlogs are correctly found if a build fails on Travis #173 Add quotes to fix icepack.setup script problem on Mac OS X #175 Have the driver read the grid namelist #196 Correct biogeochemistry tests #199 #203 Fix restart failures associated with SST restoring #201 Remove faulty logic in atmo #196 Fix time level inconsistency in transport #222 Fix intent(inout) in shortwave_dEdd_set_snow #227 Do not reinitialize parameters to 0 on subsequent parameter initialization calls #230
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.098 | 0.117 |
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".