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Record W4393808020 · doi:10.5281/zenodo.6582099

dynseq tracks data

2022· dataset· en· W4393808020 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typedataset
Languageen
FieldChemistry
TopicChemistry and Stereochemistry Studies
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This record contains data and models relevant to the manuscript on dynamic sequence (dynseq) genome browser tracks. See https://github.com/kundajelab/dynseq-paper for more information. It contains data for 2 vignettes: 1) <strong>beta globin:</strong> observed data for relevant experiments (bigwig), BPNet model TF/keras (h5) files trained on those experiments, predicted data from the models (bigwig) and importance scores (bigwig) from the models. 2) <strong>SPI1 variant analysis: </strong>BPNet model TF/keras (h5) files trained GM12878 ATAC-seq and SPI1 ChIP-seq in GM12878 (ENCSR000BGQ), predicted data from the models (bigwig) and importance scores (bigwig) from the models for ref and alt alleles at rs5764238.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Insufficient payload (model declined to judge)
Consensus categoriesOpen science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.654
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0060.011
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.6570.003

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 head0.070
GPT teacher head0.277
Teacher spread0.207 · 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