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Record W2129062902 · doi:10.1645/14-703.1

Anthelmintic Drug Discovery: Into the Future

2015· review· en· W2129062902 on OpenAlexaff
Timothy G. Geary, Judy A. Sakanari, Conor R. Caffrey

Bibliographic record

VenueJournal of Parasitology · 2015
Typereview
Languageen
FieldVeterinary
TopicHelminth infection and control
Canadian institutionsMcGill University
Fundersnot available
KeywordsAnthelminticDrug discoveryBiologyDrugDrug resistancePharmacologyBioinformaticsEcology

Abstract

fetched live from OpenAlex

The last half-century has provided all of the (few) drugs currently used to treat human helminthiases. Concern regarding the long-term utility of these drugs, given how readily resistance evolves in the veterinary-agricultural sector, spurs the discovery of new chemical entities. We review the approaches and technologies in use to identify anthelmintics and discuss a number of drug discovery paradigms that may prove pivotal to the next half-century of anthelmintic development.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.005
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.002

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 head0.059
GPT teacher head0.434
Teacher spread0.376 · 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

Citations121
Published2015
Admission routes1
Has abstractyes

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