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Record W4256201997 · doi:10.3410/f.734143341.793560848

Faculty Opinions recommendation of Redox-dependent rearrangements of the NiFeS cluster of carbon monoxide dehydrogenase.

2019· dataset· en· W4256201997 on OpenAlexaff
Deborah B. Zamble

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2019
Typedataset
Languageen
FieldEnergy
TopicMetalloenzymes and iron-sulfur proteins
Canadian institutionsUniversity of Toronto
FundersArgonne National LaboratoryNational Institute of General Medical SciencesAgence Nationale de la RechercheOffice of ScienceNational Institutes of HealthU.S. Department of Energy
KeywordsCarbon monoxide dehydrogenaseCarbon monoxideRedoxCluster (spacecraft)ChemistryPhotochemistryBiochemistryComputer scienceOrganic chemistryCatalysisProgramming language

Abstract

fetched live from OpenAlex

The C-cluster of the enzyme carbon monoxide dehydrogenase (CODH) is a structurally distinctive Ni-Fe-S cluster employed to catalyze the reduction of CO 2 to CO as part of the Wood-Ljungdahl carbon fixation pathway.Using X-ray crystallography, we have observed unprecedented conformational dynamics in the C-cluster of the CODH from Desulfovibrio vulgaris, providing the first view of an oxidized state of the cluster.Combined with supporting spectroscopic data, our structures reveal that this novel, oxidized cluster arrangement plays a role in avoiding irreversible oxidative degradation at the C-cluster.Furthermore, mutagenesis of a conserved cysteine residue that binds the C-cluster in the oxidized state but not in the reduced state suggests that the oxidized conformation could be important for proper cluster assembly, in particular Ni incorporation.Together, these results lay a foundation for future investigations of C-cluster activation and assembly, and contribute to an emerging paradigm of metallocluster plasticity.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0320.040

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 head0.032
GPT teacher head0.323
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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
Published2019
Admission routes1
Has abstractyes

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Same venueFaculty Opinions – Post-Publication Peer Review of the Biomedical LiteratureSame topicMetalloenzymes and iron-sulfur proteinsFrench-language works237,207