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Record W3176131733 · doi:10.11159/nddte21.lx.201

Impact of Nanoparticles on Bacteria and Mycobacteria

2021· article· en· W3176131733 on OpenAlexvenueno aff
Josef Jampílek, Martin Pisárčik

Bibliographic record

VenueProceedings of the World Congress on Recent Advances in Nanotechnology · 2021
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsnot available
FundersAgentúra na Podporu Výskumu a Vývoja
KeywordsBacteriaNanoparticleMicrobiologyMycobacteriumComputer scienceMaterials scienceNanotechnologyBiologyGenetics

Abstract

fetched live from OpenAlex

Bacterial infections represent an increasing worldwide threat. The number of untreatable diseases decreased after the 1950s due to the introduction of antimicrobial agents. However, since the 1980s, morbidity has risen again, and mortality due to respiratory infections, AIDS, COVID-19 and tuberculosis now represents about 85% of world mortality from infections. The increase in the number of new infections is caused by general immunosuppression (primarily by tumour treatment, administration of immunosuppressive agents, wide-spectrum antibiotics and corticoids), a significant increase in the number of diabetic, HIV or SARS-CoV-2 positive patients and development of resistance to commonly used drugs. The resistance of common pathogens to first-line drugs increased by up to 100% during the last decade. Moreover, the resistance of some strains to second-or third-line drugs can be found. Development of cross-resistant or multidrugresistant strains is also a great problem

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.280
Teacher spread0.269 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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
Published2021
Admission routes1
Has abstractyes

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Same venueProceedings of the World Congress on Recent Advances in NanotechnologySame topicNanoparticles: synthesis and applicationsFrench-language works237,207