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Record W4210554583 · doi:10.4337/9781839105951.00020

US FEDERAL GENOMIC DATA RELEASE AND ACCESS POLICIES

2022· book-chapter· en· W4210554583 on OpenAlexaboutno aff
Jorge L. Contreras

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2022
Typebook-chapter
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsnot available
FundersNational Institutes of Health
KeywordsDownloadGenetic dataData scienceGenomeData accessQuarter (Canadian coin)Human genomeWorld Wide WebComputer scienceBiologyGeographyDatabaseGeneticsGeneSociologyPopulation

Abstract

fetched live from OpenAlex

Researchers today have access to a vast aggregation of human and nonhuman genomic data, largely on an open access basis. According to the Joint Genome Institute's Genomes OnLine Database (GOLD), data from more than 40,000 sequencing projects around the world, representing more than 375,000 different organisms, were publicly available to researchers as of July 2020. The availability of this tremendous public resource is due, in large part, to the data release policies developed a quarter century ago, toward the beginning of the Human Genome Project (HGP), which have been carried forward, in modified form, to the present. These policies impose requirements on both the generators of data (typically the sequencing centers and other laboratories conducting genetic experiments) and the users of that data (that is, researchers who download and/or use it). This article, briefly outlines the history of such data release policies, particularly in the US and with respect to human genomic data, and provides an overview of the obligations imposed on both data generators and data users.

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)0.005
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.597
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0030.012
Research integrity0.0010.011
Insufficient payload (model declined to judge)0.0020.000

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 head0.425
GPT teacher head0.484
Teacher spread0.059 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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