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Additional file 1 of Capturing the antibiotic resistome of preterm infants reveals new benefits of probiotic supplementation

2022· article· en· W6977126901 on OpenAlexaff

Bibliographic record

VenueFigshare · 2022
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsResistomeGeneAntibiotic resistanceProbioticAntibiotics

Abstract

fetched live from OpenAlex

Additional file 1: Figure S1. Antibiotic exposure of preterm infants. Table S1. Information regarding the full-term infants. Table S2. Information regarding the subset of preterm infants. Figure S2. Sample collection and probiotic exposure of the subset of infants. Figure S3. Antibiotic exposure of the subset of preterm infants. Figure S4. Relative abundance of bacterial families in the infant gut microbiome. Figure S5. Targeted capture of resistance genes in the full set of infants. Figure S6. Targeted capture of resistance genes in the subset of infants. Figure S7. Differences in the resistome identified through RGI main at Visit 1. Figure S8. Distribution of genes detected at the AMR gene family level through RGI bwt. Figure S9. Distribution of genes detected at the AMR gene family level through RGI main. Figure S10. Differences in the resistome identified through RGI bwt in the subset at Visit 1. Figure S11. Differences in the resistome identified through RGI main in the subset at Visit 1. Figure S12. Unique genes in each infant group at various timepoints for the preterm infants. Figure S13. Unique genes in each infant group for the subset of preterm infants at various timepoints. Figure S14. Unique genes in each infant group at various timepoints for the subset of preterm infants. Figure S15. Unique ARGs, mechanisms, and families identified in preterm infants through RGI main. Figure S16. Unique ARGs, mechanisms, and families identified in the subset of preterm infants through RGI bwt. Figure S17. AMR gene families identified through RGI bwt. Figure S18. AMR gene families identified through RGI main. Figure S19. Genetic context of vancomycin resistance gene families detected in all infants. Figure S20. Genetic context of AMR families more prominent in NS infants. Figure S21. Genetic context of ANT(3”) resistance gene families detected in all infants. Figure S22. Genetic context of the ANT(6) gene family in all infants. Figure S23. Genetic context of OKP beta-lactamases detected in all infants. Figure S24. Genetic context of the APH(2”) gene family detected in all infants.

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)0.002
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.834
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.033
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.8340.122

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 head0.037
GPT teacher head0.274
Teacher spread0.236 · 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.

Study designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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