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Record W2096640177 · doi:10.1093/anatox/35.7.452

Relative Distribution of Ketamine and Norketamine in Skeletal Tissues Following Various Periods of Decomposition

2011· article· en· W2096640177 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Analytical Toxicology · 2011
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsLaurentian University
Fundersnot available
KeywordsMetaboliteDrugChemistryKetamineDecompositionPharmacologyBiologyMedicineBiochemistryAnesthesia

Abstract

fetched live from OpenAlex

Skeletal tissues (rat) were analyzed for ketamine (KET) and norketamine (NKET) following acute ketamine exposure (75 mg/kg i.p.) to examine the influence of bone type and decomposition period on drug levels. Following euthanasia, drug-free (n = 6) and drug-positive (n = 20) animals decomposed outdoors in rural Ontario for 0, 1, or 2 weeks. Skeletal remains were recovered and ground samples of various bones underwent passive methanolic extraction and analysis by GC-MS after solid-phase extraction. Drug levels, expressed as mass normalized response ratios, were compared across tissue types and decomposition periods. Bone type was a main effect (p < 0.05) for drug level and drug/metabolite level ratio (DMLR) for all decomposition times, except for DMLR after 2 weeks of decomposition. Mean drug level (KET and NKET) and DMLR varied by up to 23-fold, 18-fold, and 5-fold, respectively, between tissue types. Decomposition time was significantly related to DMLR, KET level, and NKET level in 3/7, 4/7, and 1/7 tissue types, respectively. Although substantial sitedependence may exist in measured bone drug levels, ratios of drug and metabolite levels should be investigated for utility in discrimination of drug administration patterns in forensic work.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.058
GPT teacher head0.405
Teacher spread0.347 · 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