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Record W7098201364

Design and Performance of the Infrared Beam Ports at the Canadian Light Source.

2014· article· en· W7098201364 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemistry
TopicChemical synthesis and alkaloids
Canadian institutionsnot available
Fundersnot available
KeywordsBeamlineInfraredSynchrotron radiationSpectrometerBeam (structure)Vacuum chamberWavelengthMagnetParticle acceleratorAperture (computer memory)
DOInot available

Abstract

fetched live from OpenAlex

Two types of beamlines covering the Mid- and Far-Infrared are planned [1]. One will supply light to commercial Fourier Transform Infrared (FTIR) spectrometers and microscopes for biological and industrial applications. The second will use a vacuum FTIR spectrometer and user-specific experimental attachments. The Mid-Infrared beamlines cover 2 to 25 micron wavelengths while the Far-Infrared beamline provides wavelengths beyond 25 micron. Flux and brilliance (brightness) curves for the Infrared beam lines are reported. The calculations are made to provide working values for the design, construction, and evaluation of the beamlines. Tailoring the bending magnet port size to the wavelength region of interest improves the expected performance for the Mid- and Far-Infrared. Obtaining aperture dimensions aids design of the dipole vacuum chamber and in-vacuum mirror mounts. A comparison to several Infrared beamlines in operation and to a standard thermal source is made to gauge performance. Dipole bending magnet radiation is the basis for comparison. Values obtained using standard bend radiation formulas are compared with values obtained using SRW, Synchrotron Radiation Workshop [2]. Port geometry for attaining this performance and requirements for the first optical

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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.057
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.006
GPT teacher head0.166
Teacher spread0.160 · 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
GenreMethods

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

Citations0
Published2014
Admission routes1
Has abstractyes

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