An Adolescent’s Use of Veterinary Medicines: A Case Report Exploring Addiction
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".