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Processing and Characterization of Bulk Chalcogenide Glasses Used for Waveguide Applications

2002· article· en· W2162426123 on OpenAlex
C. Lopez, Kathleen Richardson, Michelle de Castro, Sudipta Seal, Dharmendra Verma, Alfons Shulte, Clara Rivero, A. Villeneuve, Tigran V. Gastian, Karine Turcotte, A. Saliminia, Jacques M. Laniel

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

VenueJournal of the American Ceramic Society · 2002
Typearticle
Languageen
FieldMaterials Science
TopicPhase-change materials and chalcogenides
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsChalcogenideMaterials scienceHomogeneity (statistics)Raman spectroscopyChalcogenide glassCharacterization (materials science)DiffractionDifferential thermal analysisAnalytical Chemistry (journal)Thermal analysisThermalMineralogyComposite materialOpticsOptoelectronicsNanotechnologyChemistryThermodynamics

Abstract

fetched live from OpenAlex

Chalcogenide glasses (ChG) are of interest due to their optical and electronic properties for use in waveguide applications. To assess expected uniformity in films deposited from bulk glass starting materials, the extent of parent bulk glass property variation was evaluated. Resulting structural and optical properties of melt‐derived ChG's were investigated using X‐ray diffraction (XRD), Raman spectroscopy, differential thermal analysis and spectrophotometric analysis. The influence of melt size, purification, and other melting conditions on sample homogeneity were quantified and within‐melt property variation of bulk glass samples was found to be less than 5% for all parameters examined.

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)0.000
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.296

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 head0.028
GPT teacher head0.273
Teacher spread0.245 · 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