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Record W2278528299 · doi:10.3329/uhj.v10i2.26125

Study of External Measurements of Heart in Adult Bangladeshi Population

2015· article· en· W2278528299 on OpenAlexaff
Lubna Shirin, Humaira Naushaba, Mohammad Shahjahan Kabir, S M Niazur Rahman, Tahmida Yasmin, Tanbira Alam, Md Faruque

Bibliographic record

VenueUniversity Heart Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsRoyal College of Physicians and Surgeons of Canada
Fundersnot available
KeywordsMedicineCadaveric spasmPopulationHeart diseaseMean valueDemographyMale to femaleInternal medicineCardiologySurgeryEpidemiologyStatisticsMathematics

Abstract

fetched live from OpenAlex

The knowledge regarding normal physical measurement of heart is very important for proper diagnosis and management of various cardiac diseases. Heart disease is a predominant cause of disability and death among all industrialized nations. This study is to establish a standard data of different external parameters of heart of adult Bangladeshi population. The study was conducted at Department of Anatomy, Sir Salimullah Medical College, Dhaka from July 2009 to December 2009. The formalin fixed cadaveric 60 (sixty) (n=60) human hearts, 41 (forty one) male and 19 (nineteen) female were taken. The length, breadth and weight of the heart were measured and the data was analyzed statistically. The mean value of the length of the heart in male was 10.35±0.62 cm and female was 10.22±0.90 cm. The mean value of the breadth of the heart was 7.45±0.73 cm and 7.35±0.65 cm in male and female respectively. The mean value of the weight of the heart was 174.15±15.49 gm in male, where as for female the mean was 171.58±19.16 gm. The comparison of values of above mentioned variables between male and female were done by unpaired students test and it was statistically not significant.University Heart Journal Vol. 10, No. 2, July 2014; 78-80

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.293
Teacher spread0.213 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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