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Record W7135679031

The possibilities of physical therapy in patients with gastroesophageal reflux disease

2019· dissertation· cs· W7135679031 on OpenAlexaboutno aff
Jitka Zeiselova

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2019
Typedissertation
Languagecs
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsRefluxDiseaseGERDBachelorEsophagusStomach
DOInot available

Abstract

fetched live from OpenAlex

This bachelor thesis is focused on the problematics of the Gastroesophageal Reflux Disease and on the possibilities of its treatment by physical therapy. According to The Montreal Consensus the gastroesophageal reflux disease is defined as a condition which develops when the reflux of stomach contents causes troublesome symptoms and/or complications. It ranks among the most common gastrointestinal diseases, its prevalence in Europe moves between 8,8 - 25,9 %. As the gastroesophageal reflux disease can be influenced by the patient's lifestyle we can classify it as a lifestyle disease. Theoretical part of the thesis introduces the disease, its etiopathogenesis, symptomatology, diagnostic and therapeutic possibilities. The main aim of the theoretical part is to state an overview of possible physical therapy in patients with this disease. The practical section of the thesis consists of two case reports which include examination in the beginning and at the end of the therapy and the description of the therapy itself.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.239
Teacher spread0.234 · 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 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
Published2019
Admission routes1
Has abstractyes

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