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Biofilm Bakteri pada Penderita Rinosinusitis Kronis

2018· article· id· W2799585609 on OpenAlexaboutno aff
Yolazenia Yolazenia, Bestari Jaka Budiman, Dolly Irfandy

Bibliographic record

VenueJurnal Kesehatan Melayu · 2018
Typearticle
Languageid
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsnot available
Fundersnot available
KeywordsBiofilmMicrobiologyConfocal laser scanning microscopyBiologyBacteria

Abstract

fetched live from OpenAlex

Banyak dilaporkan kegagalan pengobatan pada rinosinusitis kronis (RSK) disebabkan resistensi terhadap antibiotik. Beberapa penelitian menunjukkan bahwa biofilm bakteri berperan penting pada etiologi dan persistensi dari RSK. Penulisan tinjauan pustaka ini adalah untuk mengetahui implikasi biofilm bakteri pada penderita RSK. Rinosinusitis kronis adalah penyakit inflamasi mukosa hidung dan sinus paranasal yang berlangsung dalam waktu lebih dari 12 minggu. Biofilm adalah suatu struktur komunitas sel-sel bakteri yang ditutupi oleh matriks polimer yang dihasilkan sendiri dan menempel pada permukaan. Berbagai penelitian menunjukkan terdapatnya biofilm bakteri pada mukosa sinonasal penderita RSK dan berhubungan dengan resistensi terhadap pengobatan dengan antibiotika. Berbagai pemeriksaan untuk mendeteksi biofilm yaitu Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Confocal Scanning Laser Microscopy (CSLM), modifikasi Calgary Biofilm Device Assay, Tube Method dan Congo Red Agar Method. Beberapa terapi potensial untuk mengatasi biofilm pada RSK sedang berkembang.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.025
GPT teacher head0.290
Teacher spread0.265 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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