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Record W2061145676 · doi:10.1080/15257770802143962

Metabolism and Distribution of Guanosine Given Intraperitoneally: Implications for Spinal Cord Injury

2008· article· en· W2061145676 on OpenAlexaff
Shucui Jiang, Gemma Fischione, Patricia Guiliani, Silvia Romano, Francesco Caciagli, Patrizia DiIorio

Bibliographic record

VenueNucleosides Nucleotides & Nucleic Acids · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsMcMaster UniversityHealth Sciences CentreMcMaster University Medical Centre
Fundersnot available
KeywordsGuanosineGuanineSpinal cordEndogenySpinal cord injuryCentral nervous systemMedicinePharmacologyChemistryEndocrinologyInternal medicineAnesthesiaNeuroscienceBiochemistryBiologyNucleotide

Abstract

fetched live from OpenAlex

Intraperitoneal administration of guanosine to rats with chronic spinal cord injury stimulates remyelination and functional recovery. If guanosine produced its effects in the nervous system, it should enter it and elevate endogenous concentrations. [(3)H]-guanosine (8 mg/kg) was administered intraperitoneally to rats and its distribution and concentration in different sites determined. Guanosine rapidly entered all tissues; its concentration peaked at about 15 minutes except in adipose tissue and CNS where it continued to rise for 30 minutes. Its chief metabolic product in all sites was guanine with over twice as much guanine as guanosine present in CNS after 30 minutes.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.285
Teacher spread0.265 · 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 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

Citations25
Published2008
Admission routes1
Has abstractyes

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