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Record W2570629401 · doi:10.1186/s13029-016-0061-y

Erratum to: A bedr way of genomic interval processing

2017· erratum· en· W2570629401 on OpenAlexaff
Syed Haider, Daryl Waggott, Emilie Lalonde, Clement Fung, Fei‐Fei Liu, Paul C. Boutros

Bibliographic record

VenueSource Code for Biology and Medicine · 2017
Typeerratum
Languageen
FieldComputer Science
TopicEvolutionary Algorithms and Applications
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsComputer scienceInterval (graph theory)Data scienceInformation retrievalData miningMathematics

Abstract

fetched live from OpenAlex

[This corrects the article DOI: 10.1186/s13029-016-0059-5.].

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)0.045
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: Other · Consensus signal: none
Teacher disagreement score0.124
Threshold uncertainty score0.415

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.045
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.003
Science and technology studies0.0030.002
Scholarly communication0.0040.004
Open science0.0030.003
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.1240.087

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 head0.026
GPT teacher head0.322
Teacher spread0.296 · 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
GenreOther

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

Citations4
Published2017
Admission routes1
Has abstractyes

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