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Record W2066335775 · doi:10.1371/journal.pbio.0020317

Submission of Microarray Data to Public Repositories

2004· article· en· W2066335775 on OpenAlexaff
Catherine A. Ball, Alvis Brāzma, Helen C. Causton, Steve Chervitz, Ron Edgar, Pascal Hingamp, John C. Matese, Helen Parkinson, John Quackenbush, Martin Ringwald, Susanna‐Assunta Sansone, Gavin Sherlock, Paul T. Spellman, C. J. Stoeckert, Yoshio Tateno, Ronald C. Taylor, Joseph White, Neil Winegarden

Bibliographic record

VenuePLoS Biology · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene expression and cancer classification
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsContext (archaeology)BiologyMicroarray databasesChecklistMicroarray analysis techniquesData scienceWorld Wide WebLibrary scienceBioinformaticsGeneticsGeneComputer scienceGene expression

Abstract

fetched live from OpenAlex

DOAJ is a unique and extensive index of diverse open access journals from around the world, driven by a growing community, committed to ensuring quality content is freely available online for everyone.

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)0.038
metaresearch head score (Gemma)0.124
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.388

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.124
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0160.021
Science and technology studies0.0060.002
Scholarly communication0.0140.009
Open science0.0060.010
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.1160.171

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 head0.062
GPT teacher head0.306
Teacher spread0.244 · 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
DomainReproducibility
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

Citations122
Published2004
Admission routes1
Has abstractyes

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