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Record W2904840441 · doi:10.1002/smll.201870238

Heat Conversion: Highly Efficient Copper Sulfide‐Based Near‐Infrared Photothermal Agents: Exploring the Limits of Macroscopic Heat Conversion (Small 49/2018)

2018· article· en· W2904840441 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

VenueSmall · 2018
Typearticle
Languageen
FieldChemistry
TopicPigment Synthesis and Properties
Canadian institutionsMcGill UniversityInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsPhotothermal therapyMaterials scienceCopper sulfideNanoparticleCopperInfraredNanotechnologySulfidePlasmonChemical engineeringOptoelectronicsOpticsMetallurgy

Abstract

fetched live from OpenAlex

In article number 1803282, Patrizia Canton, Fiorenzo Vetrone, and co-workers synthesize, via a green approach, water-dispersible plasmonic copper sulfide nanoparticles as highly efficient light-to-heat transducers featuring a readily tailorable surface. Upon comparing the results from the experimental assessment and mathematical modelling of the nanoparticles' optical and photothermal properties, the limitations of the macroscopic methods for heat conversion efficiency evaluation are discussed.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.037
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.068
GPT teacher head0.243
Teacher spread0.175 · 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