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Record W7132024735

Determinación de la presencia de bacterias del género Vibrio en la piel de la rana gigante del Titicaca (Telmatobius culeus) de vida libre

2021· dissertation· es· W7132024735 on OpenAlexaboutno aff
Gabriela Alexandra Tuesta Reyna

Bibliographic record

VenueUniversidad Peruana Cayetano Heredia Institutional Repository · 2021
Typedissertation
Languagees
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsnot available
Fundersnot available
KeywordsVibrio alginolyticusVibrioPathogenicityNova scotia
DOInot available

Abstract

fetched live from OpenAlex

Uno de los factores de la rápida disminución de la población de la rana gigante del Titicaca (Telmatobius culeus) es la colecta ilegal para su consumo en jugos. Esta actividad es popular en Lima puesto que se le atribuyen propiedades curativas y afrodisiacas, pero es posible que microorganismos patógenos para el humano estén presentes en la piel de estas ranas, tales como Vibrio cholerae, V. alginolyticus y V. fluvialis, conocidos por ocasionar mayormente cuadros de infección a nivel intestinal. Debido a las condiciones ambientales y contaminación del lago Titicaca, se planteó la hipótesis de que estas bacterias del género Vibrio podrían estar presentes en la piel de T. culeus de vida libre. El estudio se llevó a cabo en marzo del 2018, se realizaron hisopados de la superficie cutánea de 35 ranas capturadas en dos puntos del lago (Perka Norte y Chifrón). Las muestras se enviaron al laboratorio de microbiología de la Universidad Peruana Cayetano Heredia donde se agruparon, enriquecieron y cultivaron en los medios Agar TCBS y TSA. Posteriormente se usaron pruebas bioquímicas y se enviaron al Instituto Nacional de Salud, donde se utilizó el kit API 20 E para su identificación. No se identificaron bacterias del género Vibrio. Los resultados indicaron la presencia de Aeromonas hydrophila, Shewanella putrefaciens y Shewanela spp.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.454
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.259
Teacher spread0.254 · 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 teacher head, not a consensus.

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

Explore more

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