The New Wild West: Risk, Viral Politics, and the Emergence of Epigenetics
Bibliographic record
Abstract
The risk of bodily penetration by bullets emerges as the gravest threat under this logic Since carrying firearms is the norm in our fantasies of the Wild West, saloon owners present a feeling of safety for the patrons by restricting them-if a fight breaks out, the risk of losing one's life is less probable In response to this, the United States Centers for Disease Control (CDC) and the World Health Organization release hygiene protocols regarding hand washing, the use of hand sanitizers, and antimicrobial soaps (2002, 2009) (Guideline and WHO) The concern over what epidemiologists call fomites becomes the focus;fomites are anything that can be a conduit for transmission of infectious disease between living beings (think: paper money, doorknobs, toilet seats, subway straps, stethoscopes, intravenous drip tubes, etc ) [ ]with respect to the WHO guidelines, Insufficient or very low compliance rates have been reported from both developed and developing countries (WHO) [ ]not only must governments and expert organizations provide the protocols and guidelines, but compliance must also be monitored and controlled
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".