Bibliographic record
Abstract
The next question to be addressed is: how did the virus cross species to infect humans? How did the simian immunodeficiency virus of P.t. troglodytes chimps become the human immunodeficiency virus type 1? Again, science started out with an intuition: this must have occurred through the handling of chimpanzee meat by hunters, or their wives who would cut up the animals before cooking them. We will now examine whether this theory remains plausible after reviewing the various pieces of evidence accumulated over the past decade. Hunters and their prey Hunters and/or cooks can acquire infectious agents from their prey, including primates. For instance, Herpes B virus is a rare but highly lethal infection of individuals who handle monkeys, and especially laboratory technicians working with rhesus and cynomolgus macaques. Monkeypox is a smallpox-like but benign viral infection associated with exposure to monkeys. Highly lethal Ebola and Marburg haemorrhagic fevers have been reported in veterinarians and villagers who handled the carcasses of apes that had died in the wild from these infections. Recently, a retrovirus called simian foamy virus (SFV) has been associated with human exposure to monkeys and apes, and its sequencing allows the identification of the exact simian source. American veterinarians and animal caretakers working in primate centres or zoos were found to be infected with SFV acquired from chimpanzees. Fortunately, this virus does not seem to be pathogenic for humans, and no person-to-person transmission has ever been documented.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.041 | 0.011 |
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".