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.
Bibliographic record
Abstract
The use of drugs for recreational purposes is widespread. The drugs used can be divided into groups including stimulants (cocaine, amphetamines, etc.), opiates and opioids (heroin, oxycodone, methadone, fentanyl, etc.), sedatives (benzodiazepines and related substances) and miscellaneous drugs, including ketamine and cannabis (marijuana). These drugs can have profound effects on all organ systems in the body. The method of administration, whether by injection or inhalation, can cause localized and systemic effects, including the transmission of infection and granulomata at the site of injection and in the lungs. Suppurative abscesses from injection can result in systemic amyloidosis. Stimulants have profound effects on the cardiovascular and cerebrovascular systems, with enlarged hearts with fibrosis seen microscopically and cerebral infarction and haemorrhage. Crack cocaine use is also associated with changes in the pulmonary system, including carbon pigmented intra-alveolar macrophages, emphysema and pulmonary arterial changes. Cannabis use is associated with brown pigmented macrophages in the lung as well as changes in the respiratory tract epithelium. Opiates/opioids are associated with inhalational pneumonitis and hypoxic brain damage due to their respiratory depressant effects. Heroin use has been associated with focal segmental glomerulonephritis (heroin-associated nephropathy: HAN). 3,4-Methylenedioxymethamphetamine (MDMA; ecstasy) use is associated with changes in the cardiovascular system. Its use can lead to hyperpyrexia, which results in systemic changes. Ketamine abuse has been associated with cystitis. Drugs of abuse may affect testicular function. In analysing the effects of drugs at autopsy a systematic approach to sampling of histology is required.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it