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Record W3120829943 · doi:10.1080/02791072.2021.1873466

An Adolescent’s Use of Veterinary Medicines: A Case Report Exploring Addiction

2021· article· en· W3120829943 on OpenAlexaff
Mark Mohan Kaggwa, Sympson Nuwamanya, Scholastic Ashaba, Godfrey Zari Rukundo, Sheila Harms

Bibliographic record

VenueJournal of Psychoactive Drugs · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsContext (archaeology)PsychiatryAddictionMedicineSubstance abusePsychosocialPsychologyClinical psychology

Abstract

fetched live from OpenAlex

This case report describes a 17-year-old high school student serious suicide attempt using an injectable composite of veterinary medications (vitamins, vaccines, antibiotics, and antihelminthics) typically used to treat chickens. The use of this particular substance and the route of administration was novel as a method for suicide lethality and there have been no previous cases of this kind. However, this youth also developed chronic self-harming behaviors where she would repeatedly self-inject the veterinarian medication composite which included substances that were largely inert but did have a potential neuropsychiatric side effect profile that complicated her psychiatric presentation. In this context of chronically injecting a substance with unclear psychoactive properties, an interesting set of symptoms and behaviors emerged that required diagnostic clarification and interpretation. Diagnostic considerations for this youth included major depressive disorder with psychotic features, a possible emerging borderline personality disorder, post-traumatic stress disorder (PTSD), as well a possibility of an unknown substance use disorder using the veterinary medication composite. The purpose of this case study is to highlight the clinical course and explore sociocultural factors, including family and interpersonal relationships as contextually important variables.

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 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 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 score0.391
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

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

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 head0.097
GPT teacher head0.405
Teacher spread0.309 · 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 teacher head, 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

Citations15
Published2021
Admission routes1
Has abstractyes

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