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Record W1996486782 · doi:10.3390/pathogens2010033

Targeting Plasmodium falciparum Hsp90: Towards Reversing Antimalarial Resistance

2013· review· en· W1996486782 on OpenAlexafffund
Dea Shahinas, Asongna Folefoc, Dylan R. Pillai

Bibliographic record

VenuePathogens · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of CalgaryUniversity of Toronto
FundersCalgary Laboratory Services
KeywordsPlasmodium falciparumMalariaChloroquineHsp90ArtesunateDrug resistanceReversingAntimalarial AgentBiologyArtemisininVirologyFirst lineHeat shock proteinImmunologyPharmacologyMedicineMicrobiologyGeneticsGene

Abstract

fetched live from OpenAlex

Malaria continues to exact a great human toll in tropical settings. Antimalarial resistance is rife and the parasite inexorably develops mechanisms to outwit our best drugs, including the now first-line choice, artesunate. Novel strategies to circumvent resistance are needed. Here we detail drug development focusing on heat shock protein 90 and its central role as a chaperone. A growing body of evidence supports the role for Hsp90 inhibitors as adjunctive drugs able to restore susceptibility to traditionally efficacious compounds like chloroquine.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.046
GPT teacher head0.336
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), 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

Citations44
Published2013
Admission routes2
Has abstractyes

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