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Record W2792523577 · doi:10.1002/cphc.201701223

The Controversial Orientation of Adenine on Gold and Silver

2018· review· en· W2792523577 on OpenAlex
Scott G. Harroun

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

VenueChemPhysChem · 2018
Typereview
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsRaman spectroscopyContext (archaeology)Scanning tunneling microscopeOrientation (vector space)SpectroscopyDensity functional theoryChemistryInfrared spectroscopyNanotechnologyMaterials scienceOpticsPhysicsComputational chemistryOrganic chemistryQuantum mechanics

Abstract

fetched live from OpenAlex

In which orientation does adenine adsorb on gold and silver surfaces? This question has been a matter of debate for over 30 years. Since the dawn of surface-enhanced Raman spectroscopy (SERS); it and other techniques such as tip-enhanced Raman spectroscopy (TERS), surface-enhanced infrared absorption spectroscopy (SEIRAS), scanning tunneling microscopy (STM), density functional theory (DFT) simulations, and more, have been used in many attempts to answer this seemingly straightforward, yet controversial, question. Herein, the timeline and recent advances on this topic are explored, and the frequently contradictory findings are put into context and 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 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 score0.845
Threshold uncertainty score0.350

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.293
Teacher spread0.262 · 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