MétaCan
Menu
Back to cohort
Record W1979794366 · doi:10.1080/152165401317291101

Amino Acids, Then and Now‐‐A Reflection on Sir Hans Krebs' Contribution to Nitrogen Metabolism

2001· article· en· W1979794366 on OpenAlexaff
John T. Brosnan

Bibliographic record

VenueIUBMB Life · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmino Acid Enzymes and Metabolism
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAmino acidMetabolismGlutamineBiochemistryGluconeogenesisAmino acid synthesisAmino acid metabolismDeaminationUreaChemistryLysineEnzyme

Abstract

fetched live from OpenAlex

H. A. Krebs made an enormous contribution to our knowledge of amino acid metabolism, beginning with his studies on proteolysis in the early 1930s, progressing through his work on urea synthesis to an extensive series of papers on deamination and, then, to work on gluconeogenesis from amino acids. This paper addresses three of Krebs' early contributions-urea synthesis, glutamine metabolism, and D-amino acid oxidase-and relates them to our modern understanding of amino acid metabolism.

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)0.003
metaresearch head score (Gemma)0.004
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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0030.006
Open science0.0010.002
Research integrity0.0030.010
Insufficient payload (model declined to judge)0.0030.002

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 head0.013
GPT teacher head0.265
Teacher spread0.252 · 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
GenreReview

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

Citations41
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueIUBMB LifeSame topicAmino Acid Enzymes and MetabolismFrench-language works237,207