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Record W2779019546 · doi:10.1016/s1473-3099(17)30753-3

Discovery, research, and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis

2017· article· en· W2779019546 on OpenAlexafffund
Evelina Tacconelli, Elena Carrara, Alessia Savoldi, Stephan Harbarth, Marc Mendelson, Dominique L. Monnet, Céline Pulcini, Gunnar Kahlmeter, Jan Kluytmans, Yehuda Carmeli, Marc Ouellette, Kevin Outterson, Jean B. Patel, Marco Cavaleri, Edward Cox, Chris R Houchens, M. Lindsay Grayson, Paul Hansen, Nalini Singh, Ursula Theuretzbacher, Nicola Magrini, Aaron O. Aboderin, Seif Al-Abri, Nordiah Awang Jalil, Nur Benzonana, Sanjay Bhattacharya, Adrian Brink, Francesco Burkert, Otto Cars, Giuseppe Cornaglia, Oliver J. Dyar, Alex W. Friedrich, Ana Cristina Gales, Sumanth Gandra, Christian G. Giske, Debra A. Goff, Herman Goossens, Thomas Gottlieb, Manuel Guzmán Blanco, Waleria Hryniewicz, Deepthi Kattula, Timothy Jinks, Souha S. Kanj, Lawrence D. Kerr, Marie-Paule Kiény, Yang Soo Kim, Roman S. Kozlov, Jaime Labarca, Ramanan Laxminarayan, Karin Leder, Leonard Leibovici, Gabriel Levy-Hara, Jasper Littman, Surbhi Malhotra‐Kumar, Vikas Manchanda, Lorenzo Moja, B Ndoye, Angelo Pan, David L. Paterson, Mical Paul, Haibo Qiu, Pilar Ramón-Pardo, Jesús Rodríguez‐Baño, Maurizio Sanguinetti, Sharmila Sengupta, Mike Sharland, Massinissa Si-Mehand, Lynn L. Silver, Wonkeung Song, Martin Steinbakk, Jens Thomsen, Guy Thwaites, J W van der Meer, Nguyễn Văn Kính, Silvio Vega, María Virginia Villegas, Agnes Wechsler-Fördös, Heiman Wertheim, Evelyn Wesangula, Neil Woodford, Fidan O Yilmaz, Anna Zorzet

Bibliographic record

VenueThe Lancet Infectious Diseases · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsUniversité LavalCanadian Institutes of Health Research
FundersMerck Sharp and DohmeShionogiPublic Health Agency of CanadaWellcome TrustRocheBiomedical Advanced Research and Development AuthorityInnovative Medicines InitiativeGlaxoSmithKlineWorld Health OrganizationAstraZenecaPfizer
KeywordsAntibiotic resistanceAcinetobacter baumanniiEnterococcus faeciumAntibioticsMedicineTigecyclineAcinetobacterMicrobiologyBiologyBacteriaPseudomonas aeruginosa

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.010
metaresearch head score (Gemma)0.016
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: none
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.003
Science and technology studies0.0020.004
Scholarly communication0.0070.007
Open science0.0010.004
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0080.003

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 head0.040
GPT teacher head0.311
Teacher spread0.271 · 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

Citations6,087
Published2017
Admission routes2
Has abstractno

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