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Record W6980938129

Définition du profil de distribution de pathogènes responsables d’infections nosocomiales selon la niche écologique de l’environnement évier et la physico-chimie

2021· dissertation· fr· W6980938129 on OpenAlexaboutno aff

Bibliographic record

VenueEspaceINRS Institutional Digital Repository (Institut National de la Recherche Scientifique) · 2021
Typedissertation
Languagefr
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsStenotrophomonas maltophiliaIntensive careCross infectionGram-negative bacterial infectionsNiche
DOInot available

Abstract

fetched live from OpenAlex

Les infections nosocomiales résident en un problème majeur dans les unités de soins intensifs néonatals (USIN), en particulier chez les nouveau-nés prématurés. Étant un réservoir important de pathogènes opportunistes (POs), l’environnement évier des hôpitaux a souvent été identifié comme étant l’une des principales sources de transmission des infections nosocomiales. Par ailleurs, la niche écologique de l’environnement évier et les paramètres physico-chimiques de l’eau peuvent avoir une influence non négligeable sur le développement de ces PO. Les recherches effectuées dans le cadre de cette maîtrise se sont intéressées à caractériser la niche écologique de l’environnement évier et la physico-chimie de l’eau de l’USIN d’un hôpital de Montréal afin d’évaluer leur impact sur le développement de trois PO, Pseudomonas aeruginosa, Serratia marcescens et Stenotrophomonas maltophilia. Ainsi, des corrélations intéressantes ont été obtenues entre la physico-chimie, les communautés bactériennes et l’occurrence des PO dans les éviers. Il alors été possible de confirmer que, de tous les facteurs pouvant avoir un impact sur le développement des PO dans les réseaux d’eau, le principe d’exclusion de niche écologique et la physico-chimie étaient des paramètres non négligeables à prendre en compte pour expliquer le profil de distribution des PO. Nosocomial infections are a major problem in neonatal intensive care units (NICUs), especially in preterm neonates. As an important reservoir of opportunistic pathogens (OPs), the hospital sink environment has often been identified as one of the main sources of nosocomial infections transmission. In addition, the ecological niche of the hospital sink environment and the physico-chemical parameters of the water can have a significant influence on the development of these OP. The research carried out in the context of this master’s degree was aimed at characterizing the hospital sink environment and the physicochemical properties of water in the NICU of a Montreal hospital in order to assess their impact on the development of three OP, Pseudomonas aeruginosa, Serratia marcescens et Stenotrophomonas maltophilia. Thus, interesting correlations have been obtained between physicochemical features of water, bacterial communities in the sink environment and the occurrence of OP in sinks. The results suggest that the niche exclusion mechanisms and physicochemical properties of water are drivers of OP distribution profile.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.085
GPT teacher head0.407
Teacher spread0.322 · 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 designObservational
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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