MétaCan
Menu
Back to cohort
Record W2019220432 · doi:10.1093/pasj/59.sp2.s411

Near-Infrared and Mid-Infrared Spectroscopy with the Infrared Camera (IRC) for AKARI

2007· article· en· W2019220432 on OpenAlexaff
Youichi Ohyama, Takashi Onaka, Hideo Matsuhara, Takehiko Wada, Woojung Kim, Naofumi Fujishiro, Kazunori Uemizu, Itsuki Sakon, Martin Cohen, Miho N. Ishigaki, Daisuke Ishihara, Yoshifusa Ita, Hirokazu Kataza, Toshio Matsumoto, Hiroshi Murakami, Shinki Oyabu, Toshihiko Tanabé, Toshinobu Takagi, Munetaka Ueno, Hidenori Watarai, Chris Pearson, Norihide Takeyama, Tomoyasu Yamamuro, Yuji Ikeda

Bibliographic record

VenuePublications of the Astronomical Society of Japan · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsCybernet Systems Corporation (Canada)
Fundersnot available
KeywordsPhysicsInfraredSpectrographOpticsSpectroscopySatelliteSpectral resolutionInfrared spectroscopyRemote sensingAstronomySpectral line

Abstract

fetched live from OpenAlex

Abstract The Infrared Camera (IRC) is one of the two instruments on board the AKARI satellite, In addition to deep imaging from 1.8 to 26.5 $\mu$m for the pointed observation mode of the AKARI, it has a spectroscopic capability in its spectral range. By replacing the imaging filters by transmission-type dispersers on the filter wheels, it provides low-resolution ($\lambda$/$\delta \lambda \sim$ 20–120) spectroscopy with slits, or in a wide imaging field-of-view (approximately 10$\;\times\;$10). The IRC spectroscopic mode is unique for space infrared missions in that it has the capability to perform sensitive wide-field spectroscopic surveys in the near-and mid-infrared wavelength ranges. This paper describes the specifications of the IRC spectrograph and its in-orbit performance.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0290.011

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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations127
Published2007
Admission routes1
Has abstractyes

Explore more

Same venuePublications of the Astronomical Society of JapanSame topicStellar, planetary, and galactic studiesFrench-language works237,207