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Record W2947056658 · doi:10.1039/c9sc00343f

Exploring the dual functionality of an ytterbium complex for luminescence thermometry and slow magnetic relaxation

2019· article· en· W2947056658 on OpenAlexafffund
Gabriel Brunet, Riccardo Marin, Melissa-Jane Monk, Ute Resch‐Genger, Diogo A. Gálico, Fernando A. Sigoli, Elizaveta A. Suturina, Eva Hemmer, Muralee Murugesu

Bibliographic record

VenueChemical Science · 2019
Typearticle
Languageen
FieldMaterials Science
TopicMagnetism in coordination complexes
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São PauloDeutsche ForschungsgemeinschaftConselho Nacional de Desenvolvimento Científico e TecnológicoUniversity of Ottawa
KeywordsYtterbiumLuminescenceRelaxation (psychology)Magnetic relaxationDual (grammatical number)Materials scienceNanotechnologyNuclear magnetic resonanceOptoelectronicsPhysicsDopingMagnetic fieldPsychologyMagnetizationNeuroscience

Abstract

fetched live from OpenAlex

-based complex. Moreover, we correlate this anisotropic barrier with the emission spectrum of the compound, wherein we provide a complete assignment of the energetic profile of the complex. Such studies lay the foundation for the design of exciting multi-faceted materials that are able to retain information at the single-molecule level and possess built-in thermal self-monitoring capabilities.

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.078
GPT teacher head0.277
Teacher spread0.200 · 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".

Quick stats

Citations112
Published2019
Admission routes2
Has abstractyes

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