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Record W3106263174

THE CORRELATION BETWEEN DISPERSION MEASURE AND X-RAY COLUMN DENSITY FROM RADIO PULSARS

2016· article· en· W3106263174 on OpenAlexaff
Chong-Chong He, V. M. Kaspi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsMcGill University
Fundersnot available
KeywordsPulsarPhysicsLine-of-sightAstrophysicsIonizationElectron densityX-rayDispersion (optics)Interstellar mediumLinear correlationMeasure (data warehouse)Extinction (optical mineralogy)ObservatoryLine (geometry)Absorption (acoustics)ElectronGalaxyIonOpticsGeometry
DOInot available

Abstract

fetched live from OpenAlex

Pulsars are remarkable objects that emit across the entire electromagnetic spectrum, providing a powerful probe of the interstellar medium. In this study, we investigate the relation between dispersion measure (DM) and X-ray absorption column density NH using 68 radio pulsars detected at X-ray energies with the Chandra X-ray Observatory or XMM-Newton. We find a best-fit empirical linear relation of NH (10^20 cm^-2)= 0.30+0.13-0.09 DM (pc cm^-3), which corresponds to an average ionization of 10+4-3%, confirming the ratio of one free electron per ten neutral hydrogen atoms commonly assumed in the literature. We also compare different NH estimates and note that some NH values obtained from X-ray observations are higher than the total Galactic HI column density along the same line of sight, while the optical extinction generally gives the best NH predictions.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.203
Teacher spread0.192 · 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 designObservational
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

Citations61
Published2016
Admission routes1
Has abstractyes

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