MétaCan
Menu
Back to cohort
Record W2791756032 · doi:10.6000/1927-5129.2018.14.03

Prevalence and Incidence of Staphylococcus aureus from Wound of Different Animal Species

2018· article· en· W2791756032 on OpenAlexvenueno aff
Mussarat Kumbhar, Safia Kandhro, Rehmatullah Rind, Rameez Raja Kaleri, Iqra Shafi Chandio, Tanzila Farooq, Asif Bin Rehman, Aijaz Ali Junejo, Faisal Noor Qureshi, Mathan Kumar

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2018
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsStaphylococcus aureusDonkeyStaphylococcusMicrobiologyBiologyMicrococcaceaeIncidence (geometry)Staphylococcus intermediusVeterinary medicineStaphylococcal infectionsBacteriaMedicine

Abstract

fetched live from OpenAlex

The prevalence incidence and biochemical characteristics of Staphylococcus aureus isolated from wounds of buffalos, goats, dogs, donkeys and chickens were studied during present indigestion.The highest infection of Staphylococcus aureus was found in wound samples of buffalos (70.00%). as compared to goat, (33%), dog, (3%) donkey (40%) and chicken, (46.66%) respectively. The overall pure samples with Staphylococcus auerus from the animals was recorded as 39.13% while mixed infection was observed as 34.78%. The shape of Staphylococcus auerus isolated from buffalos, goat, and chicken were cocci, spherical, round in shape and characterized as G+ve. The Staphylococcus auerus isolated from all the animals were non-motile. It is concluded that highest infections of Staphylococcus aureus was found in buffalo (70.00%), whereas highest number of Staphylococcus aureus bacterial specie was observed as compared to other bacterial species.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.297
Teacher spread0.267 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Basic & Applied SciencesSame topicWound Healing and TreatmentsFrench-language works237,207