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Record W2010699022 · doi:10.1002/pmic.200300588

Further advances in the development of a data interchange standard for proteomics data

2003· article· en· W2010699022 on OpenAlexaboutno aff
Sandra Orchard, Weimin Zhu, Randall K. Julian, Henning Hermjakob, Rolf Apweiler

Bibliographic record

VenuePROTEOMICS · 2003
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPublicationProteomicsData scienceComputer scienceLibrary sciencePolitical scienceChemistryLaw

Abstract

fetched live from OpenAlex

Abstract American Society for Mass Spectrometry 51st Annual Conference on Mass Spectrometry and Allied Topics, 8–12 June, 2003 The Protein Standards Initiative (PSI) aims to define community standards for data representation in proteomics and to facilitate data comparison, exchange and verification. Significant progress was made in advancing the design and implementation of a draft standard for exchanging experimental data from proteomics experiments involving mass spectrometry at the 51st Annual Conference of the American Society for Mass Spectrometry. In collaboration with the American Society for Tests and Measurements, the PSI propose to publish this first draft at the forthcoming HUPO 2nd World Congress in Montreal, 8–11 October 2003.

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)0.132
metaresearch head score (Gemma)0.125
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.868
Threshold uncertainty score0.699

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1320.125
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0090.010
Science and technology studies0.0030.004
Scholarly communication0.0130.031
Open science0.0100.007
Research integrity0.0060.016
Insufficient payload (model declined to judge)0.0110.011

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 head0.102
GPT teacher head0.372
Teacher spread0.270 · 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.

Study designNot applicable
DomainReporting
GenreMethods

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

Citations21
Published2003
Admission routes1
Has abstractyes

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