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Record W2330468720 · doi:10.1017/s1431927614001627

Evaluating Angular Ion Current Density for Atomically Defined Nanotips

2014· article· en· W2330468720 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

VenueMicroscopy and Microanalysis · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
Fundersnot available
KeywordsAperture (computer memory)Current densityIonIon currentIon beamOpticsBeam (structure)Acceleration voltageCurrent (fluid)Gaussian beamNormalization (sociology)VoltageGaussianMaterials sciencePhysicsAtomic physics

Abstract

fetched live from OpenAlex

In this paper we investigate methods to characterize angular current density from atomically defined gas field ion sources. We show that the ion beam emitted from a single apex atom is described by a two-dimensional Gaussian profile. Owing to the Gaussian shape of the beam and the requirement to collect the majority of the ion current, fixed apertures have inhomogeneous illumination. Therefore, angular current density measurements through a fixed aperture record averaged angular current density. This makes comparison of data difficult as averaged angular current density depends on aperture size. For the same reasons, voltage normalization cannot be performed for fixed aperture measurements except for aperture sizes that are infinitely small. Consistent determination of angular current density and voltage normalization, however, can be achieved if the beam diameter as well as total ion current are known. In cases where beam profile cannot be directly imaged with a field ion microscope, the beam profile could be extracted from measurements taken at multiple acceleration voltages and/or with multiple aperture sizes.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.935

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 head0.018
GPT teacher head0.334
Teacher spread0.316 · 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