Remarks on the Conference HIV pathogenesis, virus versus host, Alberta, Canada, March 9-14, 2014
Bibliographic record
Abstract
Combined anti-retroviral therapy has been really efficient in suppressing HIV replication, but it does not cure the infection. This is due to the permanency of integrated viral DNA in the infected cells. To achieve the HIV cure, the interaction between virus and its host needs to be extremely understood. Because of this, scientific community persists in dedicating efforts to profoundly comprehend the pathogenesis of this virus. The present work summaries important aspects discussed in the last meeting HIV-Pathogenesis, Virus vs. Host. It was held in Fairmont Banff Springs, Banff, Alberta, Canada, March 9-14. The conference debated the latest advances in the biology of HIV-1. Topics as virus entry into the cell, into the host, virus exit, virushost genetics and co-evolution, host-virus interactions and responses, reservoirs, latency, reactivation, HIV and central nervous system, animal models and HIV and the microbiome at the mucosa were updated and deeply discussed. In parallel HIV vaccines: Adaptive Immunity and Beyond meeting was celebrated. The event, part of the Keystone Symposia Global Health Series, was a singular opportunity to analyze the state of HIV research and the new challenges in the battle against HIV infection.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.059 | 0.018 |
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".