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Record W4390637186 · doi:10.1002/adpr.202470001

Photochemically Engineered Large‐Area Arsenic Sulfide Micro‐Gratings for Hybrid Diffractive–Refractive Infrared Platforms

2024· article· en· W4390637186 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

VenueAdvanced Photonics Research · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced optical system design
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsMaterials scienceOpticsAchromatic lensOptoelectronicsHolographyLens (geology)LaserPhysics

Abstract

fetched live from OpenAlex

The cover picture referring to article number 2300241 by Myungkoo Kang, Tian Gu, and co-workers showcases photochemically induced micro-gratings for a hybrid diffractive–refractive lens. These lenses, composed of diffractive and refractive elements, aim to achieve achromatic optics with significantly reduced size, weight, and power consumption. Here, metastable As2S3 chalcogenide glasses underwent direct laser writing and subsequent selective etching to create diffractive micro-gratings. The grid on the lens’ surface represents photochemically induced micro-gratings, while the surrounding residue indicates ongoing selective etching. Incident parallel beams converge into a single focal point upon passing through the lens. (Cover illustration: courtesy of Ella Maru Studio.)

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.030
GPT teacher head0.329
Teacher spread0.298 · 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