Bibliographic record
Abstract
The article contains sections titled: 1. Introduction – HIV and AIDS 1.1. HIV Cytopathogenesis and AIDS 1.2. Virus Life Cycle 1.3. Opportunities for Drug Intervention 2. Reverse Transcriptase Inhibitors 2.1. Introduction 2.2. Nucleoside Analogs 2.3. Nucleotide Analogs 2.4. Non-Nucleoside Analogs 2.5. Compounds in Development 3. Protease Inhibitors 3.1. Introduction 3.2. Hydroxyethylamine Isosteres 3.3. Hydroxyethylene Isosteres 3.4. Non-Peptidic Inhibitors 3.5. Compounds in Development 4. Entry Inhibitors 4.1. Introduction 4.2. Fusion Peptide 4.3. Compounds in Development 5. Emerging Concepts in AIDS Therapy 6. Acknowledgement The human immunodeficiency virus (HIV) has been identified as the etiologic agent causing the Acquired Immuno Deficiency Syndrome (AIDS). The currently used agents for the treatment of HIV infection mainly target two important viral enzymes or inhibit viral fusion. The nucleoside analogs prematurely terminate the transcription of the viral RNA into dsDNA by reverse transcriptase. The non-nucleoside inhibitors constitute the second class of reverse transcriptase inhibitors. HIV protease, a homodimeric enzyme, is susceptible to inhibition by peptide-like structures. The process of entry of the HIV virus into the target cell can be divided into an attachment step and a fusion step. While only one inhibitor of the fusion step, Enfuvirtide, has entered the market up to now, several small-molecule inhibitors are currently in advanced development. Important efforts are being directed at the development of vaccines that can protect against HIV infection. Continued efforts are being directed at the discovery of therapies which target other essential features of the virus' life cycle, that is, the viral enzyme integrase, the viral maturation process, and the viral infectivity factor.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.154 | 0.085 |
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".