ISMAR: A new Submillimeter Airborne Radiometer
Bibliographic record
Abstract
ISMAR (International SubMillimeter Airborne Radiometer) is a new passive remote-sensing radiometer which has been jointly funded by the UK Met Office and the European Space Agency (ESA). It contains a number of heterodyne receivers operating at frequencies between 118 and 664 GHz, some with dual polarisation. The design is modular and will allow further channels to be added in future, including 874 GHz. Submillimeter waves are very sensitive to scattering by ice particles, and the channels have been selected to allow the direct retrieval of various ice-cloud properties, including Ice Water Path (IWP) which is an important parameter in General Circulation Models (GCMs). ISMAR can also be used for surface emissivity and radiative transfer studies as it can view in multiple nadir and zenith directions. ISMAR has been developed as a satellite demonstrator for ICI (Ice Cloud Imager) due for launch in 2022 on the EUMETSAT Polar System - Second Generation satellites (EPS-SG). It can be used for testing and developing retrieval algorithms prior to launch, as well as for calibration/validation post-launch and specific scientific case studies. It is designed to operate on board the FAAM BAe-146 atmospheric research aircraft, which also carries a wide range of complementary remote-sensing and in-situ instrumentation including microwave radiometers, infra-red and visible spectrometers and cloud physics probes. The instrument is self-contained, allowing simple ground-based operation as well as the potential for installation on other aircraft. ISMAR is currently undergoing integration testing, and flight testing will take place from April 2014. An ISMAR science campaign is currently planned to take place in Goose Bay, Canada in 2015 to study the submillimeter signature of cirrus cloud.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.015 |
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".