MétaCan
Menu
Back to cohort
Record W6986274613

Parasitosis intestinal en estudiantes del nivel primario de Huancayo al 2014

2014· article· en· W6986274613 on OpenAlexaboutno aff

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMachine Learning in Bioinformatics
Canadian institutionsnot available
Fundersnot available
KeywordsStatistical significanceQuarter (Canadian coin)Test (biology)Statistical analysisParasitismDescriptive statisticsSignificant differenceRural area
DOInot available

Abstract

fetched live from OpenAlex

Objectives: To determine the level of child intestinal parasitism according to the origin area in primary level students from El Tambo, Huancayo. Methods: A correlational descriptive research. For data collection about parasitism, a serial parasitological examination of stools (EPSD) and the Graham test with observation of three different samples per student were used, corresponding to first, second and third grades primary students. For data collection concerning to the academic performance, fourth quarter teachers’ reports were employed; corresponding to first, second and third grade of primary school students during 2013 in educational institutions, 31509 Ricardo Menéndez Menéndez and 30219 Paccha, El Tambo district, Huancayo. Results: It was observed students who present pathogenic parasites at 46,20% from rural areas and 38,6% from urban areas. After the process of hypothesis testing, it was observed that there were no significant differences in relation to parasitism according to where they are from (Pearson chi-square = 0,634 GL = 1 P value = 0,426). The chi square test was used, significance at 0,05 and 95% of statistical confidence. Conclusions: There is no significant difference between the parasitism levels according to the origin area.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.241
Teacher spread0.238 · 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.

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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueDialnet (Universidad de la Rioja)Same topicMachine Learning in BioinformaticsFrench-language works237,207