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Record W4399676441 · doi:10.58578/ajstea.v2i3.3196

Anemia Due to Low-Iron Affects Cognitive Capacity of Adolescent Girls Schooling in Secondary Schools in Sokoto, Nigeria

2024· article· en· W4399676441 on OpenAlexaboutno aff
Yusuf Yahaya Miya, Thomas Murma Butuwo, Abdullateef Abdullahi A., Blessing Godwin Ukwak

Bibliographic record

VenueAsian Journal of Science Technology Engineering and Art · 2024
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsAnemiaAffect (linguistics)CognitionMedicinePediatricsPsychological interventionCognitive developmentGerontologyPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Anemia is a problem occurring due to poor iron intake or hereditary sickle cells threating public health in many adolescents and adults. Anemia is able to affect cognitive ability of people especially adolescents (youngsters). This study evaluates the effect of iron-deficiency anemia and sickle cell anemia on cognition of some adolescents schooling girls from Sokoto, Nigeria. The study consisted of recruitment of 80 girls (40 normal, and 40 anemic) subjected to Montreal Cognitive Assessment. 10 girls diagnosed with sickle cell anemia and 25 normal girls were assessed with Montreal cognitive assessment. The mean marks of the respondents were noted; therewith, chi-square test revealed significant difference at (p<0.05). The anemic girls earned less mean marks (400.0 ± 13.0) compared to the normal girls (960.0 ± 25.0). The healthy participants in the study scored higher marks (945.0 ± 10.0) than the sickle cell anemia patients (90.0 ± 3). Therefore, anemia is of the potential to affect cognitive capacity of schooling girls in Sokoto. Nutritional and related interventions are important, because poor cognition may affect education and overall potential of girls to be keys in growth and development of societies.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.230
Teacher spread0.226 · 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 designBench or experimental
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
Published2024
Admission routes1
Has abstractyes

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