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Record W2143541212 · doi:10.1051/0004-6361:20034474

Nanoengineered astronomical optics

2004· article· en· W2143541212 on OpenAlexaff
E. F. Borra, Anna M. Ritcey, Rosângela Bergamasco, Philip Laird, Julie Gingras, M. Dallaire, L. Da Silva, Hélène Yockell-Lelièvre

Bibliographic record

VenueAstronomy and Astrophysics · 2004
Typearticle
Languageen
FieldEngineering
TopicCharacterization and Applications of Magnetic Nanoparticles
Canadian institutionsUniversité Laval
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsNanometreFabricationOpticsMaterials scienceNanotechnologyInstrumentation (computer programming)CoatingOptical coatingPhysicsComputer science

Abstract

fetched live from OpenAlex

We describe a technology for the fabrication of inexpensive and versatile mirrors through the use of a new type of nanoengineered optical material composed by the spreading of a self-assembling reflective colloidal film spread at the surface of a liquid. These new reflecting liquids offer interesting possibilities for astronomical instrumentation. For example, they can replace mercury in conventional rotating liquid mirrors. The main advantages offered include extremely low cost and, by coating a viscous liquid, the possibility of tilting the mirror by a few tens of degrees. We also have coated ferromagnetic liquids with these reflecting films. The resulting surfaces can be shaped by the application of a magnetic field, yielding reflecting surfaces that can have complicated shapes that can rapidly shift with time. These inexpensive and versatile optical elements could have numerous scientific and technological applications. Among possible astronomical applications, they could be used to make large inexpensive adaptive mirrors exhibiting strokes ranging from nanometers to several millimeters.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.004
GPT teacher head0.166
Teacher spread0.162 · 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

Citations24
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueAstronomy and AstrophysicsSame topicCharacterization and Applications of Magnetic NanoparticlesFrench-language works237,207