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Record W2794524168 · doi:10.5281/zenodo.1206917

STEllAR-GROUP/hpx: HPX V1.1.0: The C++ Standards Library for Parallelism and Concurrency

2018· article· en· W2794524168 on OpenAlexaff
Hartmut Kaiser, Bryce Adelstein Lelbach aka wash, Thomas Heller, Agustín Bergé, John Biddiscombe, Mikael Simberg, Anton Bikineev, Grant Mercer, Andreas Schäfer, Adrian Serio, Taeguk Kwon, Ajai V. George, Jeroen Habraken, Matthew Anderson, Marcin Copik, Steven R. Brandt, Kevin Huck, Martin Stumpf, Daniel Bourgeois, Denis Blank, Shoshana Jakobovits, Vinay Amatya, Lars Viklund, Zahra Khatami, Devang Bacharwar, Shuangyang Yang, Erik Schnetter, Christopher Christopher, Maciej Brodowicz

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2018
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsPerimeter Institute
Fundersnot available
KeywordsConcurrencyParallelism (grammar)Computer scienceGroup (periodic table)Parallel computingProgramming languageChemistry

Abstract

fetched live from OpenAlex

Please see here for all changes: http://stellar.cct.lsu.edu/files/hpx-1.1.0/html/hpx/whats_new/hpx_1_1_0.html.

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)0.003
metaresearch head score (Gemma)0.008
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: Software · Consensus signal: Software
Teacher disagreement score0.098
Threshold uncertainty score0.328

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0050.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0980.156

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 head0.027
GPT teacher head0.261
Teacher spread0.234 · 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
GenreSoftware

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

Citations2
Published2018
Admission routes1
Has abstractyes

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