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Record W4380480556 · doi:10.1039/d3ra00991b

The role of lanthanide luminescence in advancing technology

2023· review· en· W4380480556 on OpenAlexafffund
Gabriella Tessitore, Gabrielle A. Mandl, Steven L. Maurizio, Mannu Kaur, John A. Capobianco

Bibliographic record

VenueRSC Advances · 2023
Typereview
Languageen
FieldMaterials Science
TopicLanthanide and Transition Metal Complexes
Canadian institutionsConcordia UniversityUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaConcordia UniversityUniversité Laval
KeywordsLanthanideLuminescenceNanotechnologyMaterials scienceChemistryOptoelectronicsIonOrganic chemistry

Abstract

fetched live from OpenAlex

Our society is indebted to the numerous inventors and scientists who helped bring about the incredible technological advances in modern society that we all take for granted. The importance of knowing the history of these inventions is often underestimated, although our reliance on technology is escalating. Lanthanide luminescence has paved the way for many of these inventions, from lighting and displays to medical advancements and telecommunications. Given the significant role of these materials in our daily lives, knowingly or not, their past and present applications are reviewed. A majority of the discussion is devoted to pointing out the benefits of using lanthanides over other luminescent species. We aimed to give a short outlook outlines promising directions for the development of the considered field. This review aims to provide the reader enough content to further appreciate the benefits that these technologies have brought into our lives, with the perspective of travelling among the past and latest advances in lanthanide research, aiming for an even brighter future.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.002

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 head0.025
GPT teacher head0.319
Teacher spread0.293 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations112
Published2023
Admission routes2
Has abstractyes

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