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Record W3028199323 · doi:10.1128/mra.00326-20

Thaumarchaea Genome Sequences from a High Arctic Active Layer

2020· article· en· W3028199323 on OpenAlexaffabout
Emily Wei-Hsin Sun, Sassan Hajirezaie, Mackenzie Dooner, Tatiana A. Vishnivetskaya, Alice C. Layton, Archana Chauhan, Susan M. Pfiffner, Lyle G. Whyte, T. C. Onstott, Maggie C. Y. Lau

Bibliographic record

VenueMicrobiology Resource Announcements · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsMcGill University
FundersPrinceton UniversityU.S. Department of EnergyBiological and Environmental ResearchOffice of ScienceNational Science Foundation
KeywordsPermafrostArcticMetagenomicsThe arcticGenomeActive layerArchaeaLayer (electronics)AmmoniaEnvironmental scienceEnvironmental chemistryEcologyBiologyComputational biologyOceanographyChemistryNanotechnologyGeologyBacteriaGeneGeneticsMaterials scienceBiochemistry

Abstract

fetched live from OpenAlex

The role of archaeal ammonia oxidizers often exceeds that of bacterial ammonia oxidizers in marine and terrestrial environments but has been understudied in permafrost, where thawing has the potential to release ammonia. Here, three thaumarchaea genomes were assembled and annotated from metagenomic data sets from carbon-poor Canadian High Arctic active-layer cryosols.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0240.004

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 head0.023
GPT teacher head0.223
Teacher spread0.200 · 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
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

Citations2
Published2020
Admission routes2
Has abstractyes

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