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Record W2623363576 · doi:10.17750/kmj2017-419

Structure of emergency outpatient adult visits in Naberezhnye Chelny

2017· article· en· W2623363576 on OpenAlexaboutno aff
Ildar R. Iskandarov, А. А. Гильманов

Bibliographic record

VenueKazan medical journal · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPolyclinicMedicineContingency tableQuarter (Canadian coin)Statistical significanceEmergency departmentPopulationOutpatient visitsOutpatient clinicStatistical analysisPediatricsNames of the days of the weekDemographyFamily medicineInternal medicineGeographyHealth careStatisticsEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

Aim. The study of the structure of emergency outpatient adult visits in Naberezhnye Chelny. 
 Methods. 2471 cases of primary outpatient visits for acute and chronic diseases of adult population of the city of Naberezhnye Chelny in 2011-2013 were analyzed. For statistical analysis of the data analysis of contingency tables with the assessment of statistical significance using Pearson criterion χ2 was used. The critical level of significance was set at p=0.05. 
 Results. In the studied population 48.4% of primary outpatient visits were made by males and 51.6% - by females. In the general structure of visits patients aged 50 to 59 years were prevalent. Up to a quarter of the emergency outpatients noted the beginning of the disease on the weekends and holidays. The percent of visits to the polyclinic on weekends or holidays was extremely low (3.0% in the general structure of visits), while the highest rates of emergency visits to the polyclinic by adults were observed during the first half of the week. The highest number of primary emergency visits to the polyclinic among both males and females was on Mondays (28.8%). 
 Conclusion. In the structure of visits made on Mondays and Tuesdays, the proportion of patients who became ill on weekends and holidays, amounted almost 30%.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.042
GPT teacher head0.480
Teacher spread0.438 · 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 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

Citations0
Published2017
Admission routes1
Has abstractyes

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