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Record W2473254869 · doi:10.1002/2016ja022699

Imaging thermal plasma mass and velocity analyzer

2016· article· en· W2473254869 on OpenAlexafffund
A. W. Yau, Andrew Howarth

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Calgary
FundersCanadian Space Agency
KeywordsSpectrum analyzerIonPlasmaAtomic physicsDrift velocityTime of flightOutflowIonosphereMaterials sciencePhysicsOpticsGeophysicsNuclear physics

Abstract

fetched live from OpenAlex

Abstract We present the design and principle of operation of the imaging ion mass and velocity analyzer on the Enhanced Polar Outflow Probe (e‐POP), which measures low‐energy (1–90 eV/e) ion mass composition (1–40 AMU/e) and velocity distributions using a hemispherical electrostatic analyzer (HEA), a time‐of‐flight (TOF) gate, and a pair of toroidal electrostatic deflectors (TED). The HEA and TOF gate measure the energy‐per‐charge and azimuth of each detected ion and the ion transit time inside the analyzer, respectively, providing the 2‐D velocity distribution of each major ionospheric ion species and resolving the minor ion species under favorable conditions. The TED are in front of the TOF gate and optionally sample ions at different elevation angles up to ±60°, for measurement of 3‐D velocity distribution. We present examples of observation data to illustrate the measurement capability of the analyzer, and show the occurrence of enhanced densities of heavy “minor” O ++ , N + , and molecular ions and intermittent, high‐velocity (a few km/s) upward and downward flowing H + ions in localized regions of the quiet time topside high‐latitude ionosphere.

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 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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.294
Teacher spread0.279 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations11
Published2016
Admission routes2
Has abstractyes

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