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Record W2506245889 · doi:10.1385/0-89603-077-6:29

Gas Chromatographic Analysis of Amino Acids

2003· book-chapter· en· W2506245889 on OpenAlex
Ronald T. Coutts, Jupita M. Yeung

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmino Acids · 2003
Typebook-chapter
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTaurineTyrosineAmino acidPhenylalanineTryptophanBiochemistryGlutamate receptorSerotoninChemistryInhibitory postsynaptic potentialBiologyNeuroscienceReceptor

Abstract

fetched live from OpenAlex

Amino acids are involved in many metabolic processes and in protein synthesis. In the central nervous system, they also function as neurotransmitters or neuromodulators (Davidson, 1976; Corradetti et al., 1983; Fonnum, 1981, 1984). Numerous studies have demonstrated the excitatory effects of aspartate and glutamate (Watkins and Evans, 1981); the inhibitory effects of glytine, γ–aminobutyric acid (GABA), and taurine (Schaffer et al., 1981; Lloyd et al., 1983; Roberts, 1984), and the precursor roles of tryptophan in serotonin synthesis and of tyrosine and phenylalanine in the biosyntheses of catecholamines (Sved, 1983). It is not surprising, therefore, to see an ever-increasing interest in amino acid analysis in biological samples.

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.

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), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.629
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0190.000

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 head0.012
GPT teacher head0.223
Teacher spread0.211 · 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