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Record W7008839604

Costos hospitalarios en el Hospital Nacional Adolfo Guevara Velasco de Essalud, primer trimestre 2018.

2019· dissertation· en· W7008839604 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2019
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicBusiness, Education, Mathematics Research
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Service (business)Consumption (sociology)Work (physics)Production (economics)Depreciation (economics)Hospital care
DOInot available

Abstract

fetched live from OpenAlex

The present research work entitled "HOSPITAL COSTS IN THE HOSPITAL NACIONAL 
\nADOLFO GUEVARA VELASCO ESSALUD, Q1 2018", has as a problem of what is 
\ndetermines costs in the Hospital Nacional Adolfo Guevara Velasco, first quarter 2018? and 
\nobjective determine how hospital costs in Hospital Nacional Adolfo Guevara Velasco, first 
\nquarter 2018 is structured. Post protruding in the theoretical framework is that hospital costs 
\nis the consolidated expenditure for consumption of the factors of production of each health 
\ncare center, which compared with its production allows us to obtain the average unit costs 
\nfor each service and/or specialty, in a given period. Given the diversity of performance that 
\nmakes a medical centre are divided into sectors of costs: final service, middle and general, 
\nreferenced by the (management General EsSalud) 1995. 
\nThe focus of the research is quantitative and descriptive layout of basic level, this research 
\nwork performed to analyze the factors of hospital costs in the final, intermediate care and 
\ngeneral at the National Hospital services Adolfo Guevara Velasco, first quarter 2018. The 
\nstatistical analysis of the results obtained allowed to reach the following conclusion: cost 
\nhospital in EL HOSPITAL NACIONAL ADOLFO GUEVARA VELASCO of ESSALUD, 
\nfirst quarter 2018, presents of hospital costs distributed in areas of costs, which are the final 
\ncare, intermediate care service and general service where the application of the factors of 
\nhospital costs are personnel, goods, medicines and services, without considering depreciation as mentioned in your resolution of general management N ° 1235-GG-95.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.004

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 head0.013
GPT teacher head0.289
Teacher spread0.275 · 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 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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