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Record W4310173850 · doi:10.29303/jpmpi.v5i4.2212

Sosialisasi Terkait Anemia Pada Santriwati Di Pondok Pesantren Nurul Hakim Kecamatan Kediri Kabupaten Lombok Barat

2022· article· en· W4310173850 on OpenAlexaff
Listia Sisilia Anriani, Candra Eka Puspitasari, Ima Arum Lestarini

Bibliographic record

VenueJurnal Pengabdian Magister Pendidikan IPA · 2022
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsCanadian Pharmacists Association
Fundersnot available
KeywordsBoarding schoolMedicineAnemiaIslamMenstruationPediatricsFamily medicinePsychiatryInternal medicineGeography

Abstract

fetched live from OpenAlex

Anemia is a nutritional problem that is often found throughout the world which does not only occur in developing countries but also in developed countries. Low iron intake often occurs in people who consume less diverse foods, such as protein. Iron deficiency anemia is more common in young women than young men because young women experience menstruation every month and are still in their infancy, so they need more iron intake. This activity was carried out at the Nurul Hakim Islamic Boarding School, Kediri District, West Lombok Regency in September with a target of 64 female students. This activity was carried out with the aim of increasing students' understanding of anemia. This community service activity was carried out by socializing using the lecture method, interactive discussions and filling out pretest and posttest questionnaires to see a comparison of the participants' understanding levels. The results of the service show that the understanding of the students of the Nurul Hakim Islamic boarding school towards the anemia material that has been announced has increased by 7% from the percentage of the initial pretest score of 56% and posttest of 63%.

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 categoriesMeta-epidemiology (narrow), 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 score0.062
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.023
GPT teacher head0.286
Teacher spread0.263 · 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
Published2022
Admission routes1
Has abstractyes

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