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Record W2887325555 · doi:10.1039/c8cc04341h

Probing functional self-assembled molecular architectures with solution/solid scanning tunnelling microscopy

2018· article· en· W2887325555 on OpenAlexafffund
Daling Cui, Jennifer MacLeod, Federico Rosei

Bibliographic record

VenueChemical Communications · 2018
Typearticle
Languageen
FieldEngineering
TopicSurface Chemistry and Catalysis
Canadian institutionsInstitut National de la Recherche Scientifique
FundersAustralian Research CouncilDepartment of Science and Technology of Sichuan ProvinceNatural Sciences and Engineering Research Council of CanadaGovernment of Jiangxi ProvinceCanada Research Chairs
KeywordsScanning tunneling microscopeNanotechnologyQuantum tunnellingMolecular recognitionMaterials scienceMoleculeComputer scienceChemistryOptoelectronicsOrganic chemistry

Abstract

fetched live from OpenAlex

Over the past two decades, solution/solid STM has made clear contributions to our fundamental understanding of the thermodynamic and kinetic processes that occur in molecular self-assembly at surfaces. As the field matures, we provide an overview of how solution/solid STM is emerging as a tool to elucidate and guide the use of self-assembled molecular systems in practical applications, focusing on small molecule device engineering, molecular recognition and sensing and electronic modification of 2D materials.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.243
Teacher spread0.230 · 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

Citations33
Published2018
Admission routes2
Has abstractyes

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