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Record W3037072625 · doi:10.32628/cseit1949190

Effect of flux (NH4Cl)on Y2SiO5:Dy3+ (9 mol %) nanophosphors its Characterization and Structural studies

2019· article· en· W3037072625 on OpenAlexaff
K. Dhanalakshmi, A. Jagannatha Reddy

Bibliographic record

VenueInternational Journal of Scientific Research in Computer Science Engineering and Information Technology · 2019
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsCharacterization (materials science)Flux (metallurgy)Materials scienceMineralogyChemistryChemical engineeringCrystallographyNanotechnologyMetallurgy

Abstract

fetched live from OpenAlex

Flux (NH4Cl) doped on Y2SiO5:Dy3+ phosphors were synthesized by auto ignition based low temperature Solution Combustion Synthesis (SCS) using ODH as fuel. Powder X-ray diffraction (PXRD) patterns confirm the nano sized particles corresponding to JCPDS card 36-1476. The crystallite size of the samples estimated from Scherrer's formula. SEM micrographs infer addition of flux gives the enhanced grain growth and it attains smooth surface improves the crystallinity and particle morphology of the sample. FTIR data reveals the presence of M-O bonds and Y-O bonds.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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)0.0030.000

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 head0.014
GPT teacher head0.311
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2019
Admission routes1
Has abstractno

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