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Record W1964533435 · doi:10.1063/1.1567817

Response to “Comment on ‘Ultrafast electron optics: Propagation dynamics of femtosecond electron packets’ ” [J. Appl. Phys. <b>94</b>, 803 (2003)]

2003· article· en· W1964533435 on OpenAlexaff
Bradley J. Siwick, Jason R. Dwyer, Robert E. Jordan, R. J. Dwayne Miller

Bibliographic record

VenueJournal of Applied Physics · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFemtosecondElectronPhysicsWave packetField (mathematics)Ultrashort pulseComputational physicsCondensed matter physicsQuantum mechanicsAtomic physicsLaserMathematics

Abstract

fetched live from OpenAlex

In this reply, we address the main issues raised by Qian et al. regarding our recent article [J. Appl. Phys. 92, 1643 (2002)]. In particular, we reiterate the approximations used in the development of the mean-field model and demonstrate how the form used for the on-axis potential is applicable to the study of femtosecond electron packet propagation and is not in need of correction. We also repeat our assertion that the one-dimensional (1-D) fluid model developed by Qian et al. [J. Appl. Phys. 91, 462 (2002)] overestimates space-charge-induced pulse broadening and is in qualitative disagreement with femtosecond electron packet propagation dynamics. The key differences between the mean-field and 1-D fluid model are discussed and their range of applicability is clarified.

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)0.004
metaresearch head score (Gemma)0.020
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.050
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0020.003
Open science0.0050.002
Research integrity0.0500.038
Insufficient payload (model declined to judge)0.0120.014

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 head0.007
GPT teacher head0.247
Teacher spread0.240 · 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
GenreCommentary

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

Citations13
Published2003
Admission routes1
Has abstractyes

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