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Record W2130810176 · doi:10.1093/nar/gkt392

A new reference implementation of the PSICQUIC web service

2013· article· en· W2130810176 on OpenAlexafffund
Noemí del‐Toro, Marine Dumousseau, Sandra Orchard, Rafael C. Jiménez, Eugenia Galeota, Guillaume Launay, Johannes B. Goll, Karin Breuer, Keiichiro Ono, Łukasz Salwiński, Henning Hermjakob

Bibliographic record

VenueNucleic Acids Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsSimon Fraser University
FundersNational Institute of General Medical SciencesNational Heart, Lung, and Blood InstituteNational Institutes of HealthCanadian Institutes of Health ResearchEuropean CommissionGenome British Columbia
KeywordsComputer scienceWeb serviceWorld Wide WebLoginServerService (business)Web Coverage ServiceInterface (matter)XMLDatabaseWeb standardsWeb mappingOperating system

Abstract

fetched live from OpenAlex

The Proteomics Standard Initiative Common QUery InterfaCe (PSICQUIC) specification was created by the Human Proteome Organization Proteomics Standards Initiative (HUPO-PSI) to enable computational access to molecular-interaction data resources by means of a standard Web Service and query language. Currently providing >150 million binary interaction evidences from 28 servers globally, the PSICQUIC interface allows the concurrent search of multiple molecular-interaction information resources using a single query. Here, we present an extension of the PSICQUIC specification (version 1.3), which has been released to be compliant with the enhanced standards in molecular interactions. The new release also includes a new reference implementation of the PSICQUIC server available to the data providers. It offers augmented web service capabilities and improves the user experience. PSICQUIC has been running for almost 5 years, with a user base growing from only 4 data providers to 28 (April 2013) allowing access to 151 310 109 binary interactions. The power of this web service is shown in PSICQUIC View web application, an example of how to simultaneously query, browse and download results from the different PSICQUIC servers. This application is free and open to all users with no login requirement (http://www.ebi.ac.uk/Tools/webservices/psicquic/view/main.xhtml).

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)0.012
metaresearch head score (Gemma)0.014
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: none
Teacher disagreement score0.028
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.014
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0050.005
Open science0.0060.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0280.031

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 head0.035
GPT teacher head0.338
Teacher spread0.303 · 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

Citations106
Published2013
Admission routes2
Has abstractyes

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