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Evaluasi Program Penanggulangan TBC Di Daerah Istimewa Yogyakarta (Studi pada Dinas Kesehatan DIY)

2022· article· en· W4386109180 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMultidisciplinary Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryQuarter (Canadian coin)Tuberculosis controlControl (management)Observational studyTuberculosisPolitical scienceEngineeringEnvironmental healthManagementMedicineGeographyLawEconomics

Abstract

fetched live from OpenAlex

Tuberculosis control in Indonesia has made a lot of progress, but nationally the Special Region of Yogyakarta (DIY) until the second quarter of 2022, Treatment Coverage ranks 13th, which is 24.6% (SITB, 2022). It is estimated that 9,000 TB cases must be found and treated. This study aims to evaluate the implementation of the TB control program in DIY. Assessment is carried out on process and output aspects in DIY mid-2022. This observational research was conducted at the DIY Health Office. The analysis was carried out descriptively on the process and output variables by comparing the results with the targets or standards set by the Ministry of Health. The 3 main indicators of TB elimination in DIY have not achieved the target, but the activities for the Prevention and Control of Tuberculosis (P2TB) in DIY have been going quite well.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, 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 score0.142
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.368
Teacher spread0.329 · 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