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Case Study: Distribution and Redistribution of Levomepromazine and its Metabolites in a Fatal Poisoning

2003· article· en· W2077823890 on OpenAlexvenueno aff
Małgorzata Kłys, Beata Bujak-Giżycka, Wiesława Klementowicz, Julia Vanessa Kunz

Bibliographic record

VenueCanadian Society of Forensic Science Journal · 2003
Typearticle
Languageen
FieldChemistry
TopicAnalytical Methods in Pharmaceuticals
Canadian institutionsnot available
Fundersnot available
KeywordsLevomepromazineXenobioticForensic toxicologyToxicokineticsToxicologyChemistryEnvironmental chemistryPhysiologyPharmacologyMedicineChromatographyInternal medicineBiologyToxicityBiochemistry

Abstract

fetched live from OpenAlex

The subject of the study is a fatal poisoning with levomepromazine. A toxicological investigation carried out by means of the liquid chromatographic method with mass detection (LC/MS) revealed levomepromazine and its 24 metabolites in postmortem specimens in various concentrations depending on the specimen tested. The study was undertaken not only for judicial evidence, but also to investigate whether any changes occur in the concentrations of xenobiotics found in blood during the postmortem interval. The investigation confirmed such differences in xenobiotic concentrations, proving that the passive diffusion of xenobiotics in a body takes place.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0050.003
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.048
GPT teacher head0.349
Teacher spread0.301 · 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 designCase report
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

Citations4
Published2003
Admission routes1
Has abstractyes

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