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Record W2522128811 · doi:10.1021/cen-v083n023.p007

SINGLE-MOLECULE CONDUCTIVITY

2005· article· en· W2522128811 on OpenAlexaboutno aff
MITCH JACOBY

Bibliographic record

VenueChemical & Engineering News · 2005
Typearticle
Languageen
FieldChemistry
TopicVarious Chemistry Research Topics
Canadian institutionsnot available
Fundersnot available
KeywordsElectronicsMolecular electronicsNanotechnologyElectronic materialsElectronic circuitEngineeringEngineering physicsElectrical engineeringMoleculeMaterials sciencePhysics

Abstract

fetched live from OpenAlex

RESEARCHERS IN CANADA have discovered a new way to control the flow of electrical urrent through individual molecules. The study broadens understanding of fundamental molecular processes and may hasten development of singje-moleculebased detectors and other types of molecular electronic devices. Electronic circuits based on just a few molecules hold the promise of advancing today's miniaturized silicon-based electronics to even smaller, faster, and more densely packed electronic components. But taking the big step toward tiny electronic devices requires detailed understanding and unprecedented control of the flow of current through individual molecules. A new method for exerting that type of control over singlemolecule conductivity has just been demonstrated by a team of researchers at the University of Alberta and the Canadian National Research Council's Institute for Nanotechnology in Edmonton. Postdoctoral associate Paul G. Piva, physics professor Robert A. Wolkow, and their colleagues have shown that ...

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.021
GPT teacher head0.246
Teacher spread0.226 · 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
GenreOther

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

Citations0
Published2005
Admission routes1
Has abstractyes

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