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Record W2883285116 · doi:10.4103/jfmpc.jfmpc_110_18

Analysis of tuberculosis case report in Hyderabad district of Telangana state

2018· article· en· W2883285116 on OpenAlexaboutno aff
Snigdha Pattnaik

Bibliographic record

VenueJournal of Family Medicine and Primary Care · 2018
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTuberculosisPopulationPublic healthPrivate sectorQuarter (Canadian coin)Environmental healthEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: The estimated incidence of TB in India was approximately 28,00,000 as per the Global TB report 2017. This accounts for a quarter of the world's TB (Tb) cases. National strategic plan, is a programme which aims at the elimination of Tb by 2018. The programme is crafted in line with other health sector strategies and global efforts, such as the draft National Health Policy 2015, World Health Organization's (WHO) End TB Strategy and the Sustainable Development Goals (SDGs) of the United Nations (UN). Key strategies under National Strategic plan: Private sector engagement, active case finding, drug resistant Tb case management, addressing social determinants including nutrition, robust surveillance system, community engagement and multisectoral approach. METHODS: In March 2018, India Tb report was released by RNTCP. An analysis of the report is done in the research article, an attempt to take forward end Tb strategy. RESULT: According to The India Tb report, 85% of new TB cases were detected, nationwide, where as 90% of new cases were detected in Hyderabad, during the same time period. Tuberculosis (Tb) notification rate (per 100 000 population), in India is 138, where as in Hyderabad district of Telengana it is 100. Both Public and private sector Tb case notification rate, of Hyderabad district was less than that of India (90,10). 6% of Tb cases were paediatric cases both Hyderabad and Nationwide. HIV status was known in 66% cases, in India and 67% in Hyderabad district of Telengana.

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 score0.085
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.050
GPT teacher head0.369
Teacher spread0.319 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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