Bibliographic record
Abstract
The outstanding issue regarding recent trends in the epidemiology of infectious diseases is the epidemic occurrence of severe acute respiratory syndrome (SARS) in 2003. SARS is caused by a novel coronavirus, presumably originating from wild cats. This new agent was rapidly identified and characterized, the outbreak was terminated in early summer 2003 after implementation of strict infectious control measures. Especially the high rate of complications and nosocomial infections has caused severe public health problems in China and Canada. The number of persons infected with HIV is still rising rapidly globally. New regions with rapid spread include the countries of the former Soviet Union in East Europe and Central Asia. The introduction of modem antiretroviral therapy in countries with high prevalence is making slow progress, with no visible impact on transmission dynamics so far. The WHO has implemented a number of programs to eradicate or eliminate targeted infectious diseases. Polio eradication and elimination of neonatal tetanus are making slow progress, obstacles to the control of these diseases are ongoing armed conflicts in regions with high prevalence and underfinancing of programs. Lack of funding is especially obvious regarding programs for the control and therapy of malarial infections. The numbers of patients newly identified with new variant Creutzfeldt-Jakob disease are not rising, but rather constant or even declining, making a large epidemic of vCjD unlikely.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.124 | 0.192 |
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".