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Record W4412071939 · doi:10.1117/12.3076666

Gamified laser beam measurement to attract new students in optics and photonics

2025· article· en· W4412071939 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsUniversité LavalExfo Electro-Optical Engineering (Canada)
Fundersnot available
KeywordsPhotonicsLaser beamsOpticsLaserBeam (structure)PhysicsComputer science

Abstract

fetched live from OpenAlex

The Photonic Games is an annual educational event, initiated in 2008, aimed at sparking high school students' interest in optics and photonics through interactive, science-based challenges. One such activity involves a "laser beam profiling" game, inspired by Star Wars, where participants use laser pointers and a laser beam profiler. Initially designed in LabVIEW, the game was revamped in 2024 using Python and ModernGL, enhancing both user experience and technical engagement. This new version, hosted on GitHub, features 3D starship models and space backgrounds, providing a platform for students to explore programming and optics in a hands-on environment. Participants gain practical insights into laser beam measurement concepts, including beam profiling, centroid calculation, pixel saturation, and decimation, reinforcing precision and technical skill development. By integrating professional tools and open-source programming, the Photonic Games foster an enriching, educational experience, effectively motivating students to pursue careers in engineering, physics, and related fields.

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.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.094
GPT teacher head0.442
Teacher spread0.348 · 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

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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