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Record W2972514202 · doi:10.2351/1.5118534

Laser decommissioning and practical laser training

2019· article· en· W2972514202 on OpenAlexaff
Sandu Sonoc, Gustavo Moriena

Bibliographic record

VenueInternational Laser Safety Conference · 2019
Typearticle
Languageen
FieldMedicine
TopicOcular and Laser Science Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLaserNuclear decommissioningLaser safetyPolarizerSession (web analytics)Computer scienceOpticsEngineeringPhysics

Abstract

fetched live from OpenAlex

Knowledge is the best defense. Wearing the wrong laser goggles is more dangerous than not wearing goggles at all. Misunderstanding how a polarizer or a beam splitter works has resulted in a large number of laser accidents. People learn the most when they do things. A practical session of laser safety training is considered essential. Building a laser lab for the practical session of the training can be too demanding for the budget of an Office of Health and Safety. On the other hand, the LSOs in large universities are involved in the decommissioning of many lasers and instruments containing lasers. Although such equipment is old and generally considered obsolete for research purposes they contain valuable lasers and optical components ideal for a laser-teaching lab. In this paper, the authors will present examples of recycled lasers and laser components currently used as props in the classroom during oral presentations and in the practical laser-teaching lab at our university.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.997

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)0.0040.000

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 head0.058
GPT teacher head0.372
Teacher spread0.314 · 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.

Study designObservational
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

Citations0
Published2019
Admission routes1
Has abstractyes

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