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Record W2147960554 · doi:10.1109/csb.2004.1332487

Exploring the use of stem-loop characteristics for pinpointing structural RNA genes

2004· article· en· W2147960554 on OpenAlexaff
Kirt M. Noël, Kay C. Wiese

Bibliographic record

VenueProceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004. · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsLoop (graph theory)Computational biologyMetric (unit)Stem-loopGeneRNABiologyStem cellComputer scienceGeneticsMathematicsEngineeringCombinatorics

Abstract

fetched live from OpenAlex

Our goal is to determine whether a stem-loop metric or combination of stem-loop metrics can be used to identify structural RNAs along genomic sequences across the entire GC content spectrum. Herein we describe the first step towards this goal by comparing selected stem-loop metric valuations between structural RNAs and their genomic counterparts.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.097
GPT teacher head0.254
Teacher spread0.157 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations4
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueProceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004.Same topicRNA and protein synthesis mechanismsFrench-language works237,207