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Record W2915844742 · doi:10.1039/c9na00016j

Quantification of amine functional groups on silica nanoparticles: a multi-method approach

2019· article· en· W2915844742 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNanoscale Advances · 2019
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsNational Research Council Canada
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaEnvironment and Climate Change Canada
KeywordsX-ray photoelectron spectroscopyNinhydrinReagentChemistryAmine gas treatingDissolutionNanomaterialsNanoparticleCombinatorial chemistryChemical engineeringOrganic chemistryNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

F solid state NMR and X-ray photoelectron spectroscopy (XPS). Good agreement between the assays and the determination from solid-state NMR is reinforced by elemental ratios from XPS, which indicate that in most cases the difference between total and accessible amine content reflects amines that are outside the depth probed by XPS. Overall the combined results serve to validate the relatively simple colorimetric assays and indicate that the reactions are efficient at quantifying surface amines, by contrast to some other covalent modifications that have been employed for functional group quantification.

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)0.001
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 score0.695

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.022
GPT teacher head0.274
Teacher spread0.252 · 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