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Record W203745313

Сравнительный анализ предпочтений врачей из двух регионов Беларуси при амбулаторном лечении артериальной гипертензии

2009· article· ru· W203745313 on OpenAlexaboutno aff
В. П. Вдовиченко

Bibliographic record

VenueЖурнал Гродненского государственного медицинского университета · 2009
Typearticle
Languageru
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEnalaprilPharmacotherapyFurosemideDoseQuarter (Canadian coin)Internal medicinePediatricsBlood pressureAngiotensin-converting enzymeGeography
DOInot available

Abstract

fetched live from OpenAlex

Arterial hypertension (АН) is the cardiovascular pathology most widespread in the world which treatment in many cases is carried out for life. For this reason, interest to rational treatment АГ always was big. As well as at other diseases antihypertensive therapy eventually undergoes changes. Therefore it seems to be reasonable to check doctor's viewpoint on antihypertensive therapy. Questioning is carried out in III quarter 2005 among 64 local doctors of 4 polyclinics of Grodno and in III quarter 2006 among 54 local doctors of 3 polyclinics of Gomel and Zhlobin. The purpose of it was comparison of approaches to hypertension pharmacotherapy of doctors from two regions of Belarus which divided geographically and has by a year time interval. Similar results are found out in both groups: positive (primary use ofrepresentatives of 4 basic classes ofantihypertensive drugs, combined treatment AH) and negative: the tendency of administration of too low dosages of diuretics and, partly, enalapril; wide application ofshort-acting preparations ofnifedipine, myotropic spamolytics and furosemide.

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)0.007
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0050.004
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0020.006
Science and technology studies0.0030.005
Scholarly communication0.0010.002
Open science0.0060.002
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0330.018

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 head0.046
GPT teacher head0.312
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; both teacher heads agree on what is shown here.

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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueЖурнал Гродненского государственного медицинского университетаSame topicMedical and Biological SciencesFrench-language works237,207