MétaCan
Menu
Back to cohort
Record W2147360106 · doi:10.1109/hpcs.2006.17

Connecting Researchers to HPCS through Web Services

2006· article· en· W2147360106 on OpenAlexaff
G.A. Klotz, Neil Harvey, Deborah Stacey

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsUniversity of Guelph
FundersU.S. Department of Agriculture
KeywordsUnixComputer scienceWorld Wide WebThe InternetInterface (matter)Operating systemWeb serviceUser interfaceWeb browserSoftware

Abstract

fetched live from OpenAlex

Researchers may find it difficult to run experiments on High Performance Computing Systems (HPCS) if they are unfamiliar with terminals and UNIX/Linux commands. Instead of using available HPCS resources, they may choose to run experiments on their personal computers, even if it takes them weeks to run small jobs. However, these researchers are familiar with using the Internet on a daily basis to check email or read the latest news. To make high performance computing more accessible and to help researchers use the HPCS available to them, the authors have developed a web based interface for running simulations from a web browser. This paper describes the design of this interface and its benefits.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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 head0.282
GPT teacher head0.462
Teacher spread0.180 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations2
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicScientific Computing and Data ManagementFrench-language works237,207