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Record W2099475190 · doi:10.1139/p01-154

Studies for the Odin sub-millimetre radiometer: III. Performance simulations

2002· article· en· W2099475190 on OpenAlexvenueno aff
Frank Merino, D. Murtagh, Martin Ridal, Patrick Eriksson, Philippe Baron, Philippe Ricaud, J. de La Noë

Bibliographic record

VenueCanadian Journal of Physics · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
Fundersnot available
KeywordsAeronomyMesopausePhysicsRadiometerSatelliteRemote sensingDepth soundingThermosphereMillimeterSuperheterodyne receiverAtmospheric soundingStratosphereMeteorologyMesosphereAstronomyIonosphereAtmosphere (unit)OpticsGeographyMicrowave

Abstract

fetched live from OpenAlex

Odin is a small, low-cost satellite with a combined astronomical and aeronomical mission. The mission is divided on an equal basis between astronomy and aeronomy. The aeronomy objectives can be divided into four main subjects: stratospheric ozone chemistry, mesospheric ozone chemistry, the summer mesopause region, and the coupling between atmospheric regions. The primary instrument on Odin is the millimetre and sub-millimetre radiometer (SMR), which is used both for astronomy and aeronomy. It is the first satellite to use sub-millimetre frequencies for limb-sounding mode. Odin is also equipped with an optical spectrometer (OSIRIS). This paper is the third of a three-part series and describes the choices of observing modes and the expected performance of the SMR instrument for the aeronomy mission. The relevant frequencies are identified and the exact selection of lines is made. This is followed by a detailed simulation study to determine the achievable altitude coverage together with the corresponding vertical resolution for each retrievable species. An indication of the expected uncertainties is also given, showing, for example, a high-sensitivity to mesospheric water vapour and stratospheric chlorine monoxide. However, a complete analysis of observation uncertainties must await launch and the completion of the validation programme. PACS Nos.: 42.68A, 07.07D, 07.57K

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.051
GPT teacher head0.232
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations36
Published2002
Admission routes1
Has abstractyes

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