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Record W2602122012 · doi:10.1039/9781788010580-00001

Introduction to the Biological Chemistry of Nickel

2017· book-chapter· en· W2602122012 on OpenAlexaff
Deborah B. Zamble

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnergy
TopicMetalloenzymes and iron-sulfur proteins
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNickelCarbon monoxide dehydrogenaseHydrogenaseEnzymeChemistryBiochemistryUreaseCarbon monoxideOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Nickel ions are used as enzyme cofactors in organisms from all kingdoms of life, and these essential enzymes catalyze a variety of remarkable chemical reactions. A significant part of this book is devoted to updating our understanding of the biological chemistry of many of these nickel enzymes, including urease, [NiFe]-hydrogenase, carbon monoxide dehydrogenase and acetyl-CoA synthase, coenzyme M reduction, nickel superoxide dismutase, nickel utilizing glyoxylase I, and the most recent addition to this list, lactate racemase. However, as the content of this book underscores, the biology of nickel encompasses many components beyond the enzymes themselves, including multiple types of membrane transporters, metallochaperones, and regulators, which are critical for maintaining and distributing healthy levels of nickel. Moving even further out from the enzymes, a discussion of nickel in biology also includes the overlap of nickel pathways with the systems of other nutritional metals, aspects of human disease including carcinogenesis and pathogenic microorganisms, biogeochemistry, and, finally, potential applications of this information.

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)0.000
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.059
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0590.048

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 head0.030
GPT teacher head0.234
Teacher spread0.204 · 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
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

Citations10
Published2017
Admission routes1
Has abstractyes

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