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Record W2189738482 · doi:10.1155/2006/695698

Desperate Therapies and the Amazing Race for Antimicrobial Alternatives

2006· article· en· W2189738482 on OpenAlexaff
A. Mark Joffe

Bibliographic record

VenueCanadian Journal of Infectious Diseases and Medical Microbiology · 2006
Typearticle
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsRoyal Alexandra Hospital
Fundersnot available
KeywordsRace (biology)Arms raceAntimicrobialIntensive care medicineRisk analysis (engineering)Antibiotic resistanceMedicineBiotechnologyEngineering ethicsBusinessBiologyEngineeringEconomicsMicrobiologyPolitical economyAntibiotics

Abstract

fetched live from OpenAlex

Infectious diseases remain a leading cause of death worldwide. Despite this fact, as well as the increasing recognition that microbial resistance is emerging as a serious threat to human health, antimicrobial research and development are declining. The current situation has evolved through a complex interaction of scientific, economic and regulatory forces. New approaches are needed. If therapies are unavailable or failing, we have only two options: we can prevent infections or we can develop new strategies to deal with them.

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)0.009
metaresearch head score (Gemma)0.012
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.009
Scholarly communication0.0060.013
Open science0.0020.004
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0150.004

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 head0.006
GPT teacher head0.247
Teacher spread0.241 · 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
GenreCommentary

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

Citations0
Published2006
Admission routes1
Has abstractyes

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