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Record W4387002245 · doi:10.1128/mra.00507-23

A high-throughput structural system biology approach to increase structure representation of proteins from <i>Clostridioides difficile</i>

2023· article· en· W4387002245 on OpenAlexaff
Mónica Rosas‐Lemus, Supratim Dey, G. Minasov, Kemin Tan, Spencer Anderson, J.S. Brunzelle, Salvatore Nocadello, Ekaterina Filippova, A.S. Halavaty, Youngchang Kim, N. Maltseva, J. Osipiuk, W. Minor, A. Joachimiak, Alexei Savchenko, W.F. Anderson, K.J.F. Satchell

Bibliographic record

VenueMicrobiology Resource Announcements · 2023
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsUniversity of Calgary
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesOffice of ScienceNational Institutes of HealthMichigan Economic Development CorporationU.S. Department of Health and Human ServicesU.S. Department of Energy
KeywordsClostridioidesThroughputRepresentation (politics)Computational biologyStructural biologyComputer scienceBiologyGeneticsMicrobiologyPolitical science

Abstract

fetched live from OpenAlex

causes life-threatening gastrointestinal infections. It is a high-risk pathogen due to a lack of effective treatments, antimicrobial resistance, and a poorly conserved genomic core. Herein, we report 30 X-ray structures from a structure genomics pipeline spanning 13 years, representing 10.2% of the X-ray structures for this important pathogen.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
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
Bibliometrics0.0000.002
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 head0.023
GPT teacher head0.287
Teacher spread0.264 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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