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Record W2037167477 · doi:10.1364/ao.42.005670

Increasing the range of unambiguity in step-height measurement with multiple-wavelength interferometry—application to absolute long gauge block measurement

2003· article· en· W2037167477 on OpenAlexaffabout
J E Decker, John Miles, A.A. Madej, Ralph F. Siemsen, K.J. Siemsen, Sebastian de Bonth, Krijn Bustraan, Sara Temple, James R. Pekelsky

Bibliographic record

VenueApplied Optics · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvanced Measurement and Metrology Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsInterferometryOpticsWavelengthCalibrationPhysicsMeasurement uncertaintyInterference (communication)Context (archaeology)Length measurementRange (aeronautics)Materials scienceTelecommunicationsComputer scienceGeology

Abstract

fetched live from OpenAlex

An instrument for step-height measurement by multiple-wavelength interferometry is described. The addition of a 1152-nm wavelength to a multiple-wavelength scheme applying wavelengths of 633, 612, and 543 nm relaxes the tolerance range of the required preliminary measurement to +/- 140 microm, if the total uncertainty in the fringe fraction measurement can be kept below 2%. For larger fringe fraction measurement uncertainty, numerical simulations show that the integer number of interference orders can still be determined unambiguously if the range in the preliminary knowledge of the length has been correspondingly reduced. The interferometer instrument is described, and experimental data are presented in the context of long gauge block calibration at the National Research Council of Canada.

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)0.003
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
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.218
Teacher spread0.196 · 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

Citations56
Published2003
Admission routes2
Has abstractyes

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