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Record W2776809654 · doi:10.3847/1538-4365/aa91d3

The GALFA-H i Survey Data Release 2

2017· article· en· W2776809654 on OpenAlexaff
J. E. G. Peek, B. Babler, Yong Zheng, Susan E. Clark, Kevin A. Douglas, Eric Korpela, M. E. Putman, Snežana Stanimirović, S. J. Gibson, Carl Heiles

Bibliographic record

VenueThe Astrophysical Journal Supplement Series · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsOkanagan College
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

Abstract We present the Galactic Arecibo L-Band Feed Array H i (GALFA-H i ) survey data release 2 (DR2). The survey covers the 21 cm hyperfine transition of Galactic H i from −650 to 650 , with 0.184 channel spacing, 4′ angular resolution, and 150 mK rms noise per 1 velocity channel. DR2 covers the entirety of the sky available from the William E. Gordon 305 m antenna at Arecibo, from decl. −1°17′ to decl. + 37°57′ across all R.A.: 4 steradians or 32% of the sky. DR2 differs in a number of ways from data release 1, which was released in 2011. DR2 is built from a largely separate set of observations from DR1, which were taken in a much more consistent mode. This consistency, coupled with more careful attention to systematics and more advanced data reduction algorithms, leads to a much higher-quality DR2 data product. We present three data sets for public use: H i data cubes, far-sidelobe stray-radiation-corrected column density maps, and results of the Rolling Hough Transform linear feature detection algorithm.

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 score0.042
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0340.038

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 head0.037
GPT teacher head0.290
Teacher spread0.253 · 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

Citations113
Published2017
Admission routes1
Has abstractyes

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