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Record W2007183772 · doi:10.1063/1.2204582

Novel fiber-based integrating sphere for luminous flux measurements

2006· article· en· W2007183772 on OpenAlexafffund
Martin Szylowski, Michele Mossman, David R. Barclay, Lorne Whitehead

Bibliographic record

VenueReview of Scientific Instruments · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLuminous fluxSPHERESMeasure (data warehouse)DetectorIntegrating sphereOpticsBaffleFlux (metallurgy)Optical fiberPhysicsComputer scienceTopology (electrical circuits)Materials scienceLight sourceData mining

Abstract

fetched live from OpenAlex

Traditional integrating spheres, which use a single detector to measure luminous flux, have a number of drawbacks associated with the sources of error caused by baffling, nonideal topology, and variations in surface reflectance. In this article we address the potential drawbacks of many traditional integrating spheres and present a new instrument which achieves accurate measurements without the use of baffles, by relying on optical fibers to distribute measurement points around the interior of a highly reflective structure.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.037
GPT teacher head0.271
Teacher spread0.234 · 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

Citations7
Published2006
Admission routes2
Has abstractyes

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