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Record W6908396080 · doi:10.25919/5c30a2b3e3cc5

Parkes observations for project P995 semester 2018OCTS_02

2018· dataset· en· W6908396080 on OpenAlexaff

Bibliographic record

VenueCSIRO · 2018
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of TorontoMcGill University
Fundersnot available
KeywordsPulsarGlitchFlux (metallurgy)Pulse (music)Sensitivity (control systems)Neutron star

Abstract

fetched live from OpenAlex

We propose to perform observations of the very young pulsar PSR B0540–69 in the Large Magellanic Cloud to detect pulsed flux from this traditionally radio-quiet source. We are motivated to do so due to a relatively recent X-ray observation of a 36% change in its spin down rate, thought to be due to a state change in its magnetospheric processes. There is reason to believe this may be accompanied by an increase in pulsed flux, as has been seen in intermittent pulsar behaviour, for example. Additionally, PSR B0540–69 is known to emit giant pulses, one of only a small number of pulsars to do so. With the new Ultra Wideband Low-frequency (UWL) receiver system, we will be able to conduct the highest sensitivity observations of this source yet achieved at radio wavelengths. A successful detection of pulsed flux will provide important insight into the magnetospheric evolution and behaviour in this pulsar, and a better understanding of how its glitch behaviour may influence its emission. Even without such a detection, we will be able to study the giant pulse behaviour of PSR B0540–69 with unprecedented sensitivity.

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)0.001
metaresearch head score (Gemma)0.003
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.054
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0530.075

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 head0.167
GPT teacher head0.370
Teacher spread0.203 · 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
GenreDataset

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
Published2018
Admission routes1
Has abstractyes

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