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Record W3147959684 · doi:10.1364/ao.421294

Precise determination of the focal point on a glass sample using spectroscopy analysis

2021· article· en· W3147959684 on OpenAlexafffund
Alexander Wainwright, Luc Lévesque

Bibliographic record

VenueApplied Optics · 2021
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsRoyal Military College of CanadaQueen's University
FundersMinistère de la Défense Nationale
KeywordsOpticsNumerical apertureLaserFocal pointPoint (geometry)SpectroscopyLaser scanningMaterials scienceComputer scienceCardinal pointPhysicsMathematicsGeometry

Abstract

fetched live from OpenAlex

lasers have been used extensively to mark insulators such as glass and wood during industrial production. Usually, a system of mirrors is used during a marking procedure. Although a laser beam can be characterized accurately using well-known methods, it is desirable to identify where the focal point is after reflecting on the scanning mirrors. The positioning of a motorized stage with a knife-edge and a sensing device to characterize a beam after reflecting through a mirror scanner system is impractical due to limited space. The method described here to determine the focal point accurately requires using only a large numerical aperture fiber connected to a motorized stage. In this paper, we investigate how spectroscopy of typical emission lines can be used to identify the position of the focal point in real time during laser marking procedures.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.298
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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 teacher head, 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

Citations1
Published2021
Admission routes2
Has abstractyes

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