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Record W3159665217 · doi:10.7759/cureus.14805

Forty Years Since the Epidemic: Modern Paradigms in HIV Diagnosis and Treatment

2021· review· en· W3159665217 on OpenAlexaff
Karan Patel, Alex Zhang, Michelle Zhang, Sean Bunachita, Basil M. Baccouche, Henna Hundal, Liseth Lavado, Aakshi Agarwal, Preeti Malik, Urvish Patel

Bibliographic record

VenueCureus · 2021
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineHuman immunodeficiency virus (HIV)Intensive care medicineDiseaseImmune DysfunctionImmunologyImmune systemPathology

Abstract

fetched live from OpenAlex

Human immunodeficiency virus (HIV) is a viral infection that, when transmitted through the exchange of certain bodily fluids, destroys various immune cells and contributes to an overall weakened immune system. If left untreated, HIV progresses to acquired immunodeficiency syndrome (AIDS) - a chronic, life-threatening condition that puts patients at risk for opportunistic infections. Since the emergence of HIV nearly a century ago, the world has seen tremendous advances in elucidating its pathology and progression. These advances have been accompanied by an increased understanding of how subsequent effects and symptoms manifest in afflicted individuals. These discoveries, coupled with the ever-improving technologies and methodologies used for detection and treatment, provide the scientific and medical community with a solid grasp of HIV. Despite this significant headway, there is still much progress to be made; medical advances have allowed people with HIV to manage their disease and live a longer, healthier life, but a definite cure is yet to be found. Thus, the following literature review serves as both an extensive compendium of our current understanding of HIV - its pathology, testing/detection, repercussions, and treatment - and an acknowledgement of the areas that still require further research.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.146
GPT teacher head0.434
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations8
Published2021
Admission routes1
Has abstractyes

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