Bibliographic record
Abstract
### What you need to know A 22 year old man presented to the emergency department for HIV post-exposure prophylaxis (PEP). Twenty six hours previously, he had anal receptive intercourse without a condom with a man of unknown HIV serostatus. He had immediate testing for HIV (using a fourth generation antibody/antigen assay as recommended 12 ), hepatitis B and C serologies, syphilis serology, and urine nucleic acid amplification tests for gonorrhoea and chlamydia. In the emergency department he received a three day supply of combined emtricitabine/tenofovir disoproxil fumarate (TDF/FTC) (one tablet, daily) plus raltegravir (400 mg twice daily). He was referred to be seen urgently in the next three days in an outpatient clinic for continuing management. PEP is a safe and effective HIV prevention modality for people with a recent (within 72 hours) exposure to HIV. People with HIV exposure often present to primary care clinics and emergency departments, so it is useful for non-specialists to have confidence in prescribing PEP. Clinicians caring for people presenting with a recent HIV exposure require knowledge of recommended diagnostic testing after sexual exposure and blood borne exposure, PEP regimens, schedule of short and long term follow-up, and the potential for physical and psychological trauma (eg, in the case of sexual assault). This article offers practical advice and resources for clinicians caring for individuals who present for care after an actual or potential exposure to HIV that …
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.067 | 0.023 |
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".