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Record W2747030250

Hrvatska zdravstvena anketa 2003/10. (HZA 2003/10)

2010· article· sl· W2747030250 on OpenAlexaboutno aff
Silvije Vuletić

Bibliographic record

VenueUniversity of Zagreb University Computing Centre (SRCE) · 2010
Typearticle
Languagesl
FieldHealth Professions
TopicGlobal Health and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

Hrvatsku zdravstvenu anketu 2003. provelo je Ministarstvo zdravstva RH u suradnji sa Skolom narodnog zdravlja «Andrija Stampar» i Hrvatskim zavodom za javno zdravstvo kao dio projekta za prevenciju kardiovaskularnih bolesti financiranog kreditom Svjetske banke. Statistics Canada sudjelovala je u projektu kao konzultant za dizajn istraživanja, statisticku obradu i kvalitetu podataka. Projekt je vodio prof. S. Vuletic, uz sudjelovanje tima koji je ukljucio istraživace iz SNZ-a «A. Stampar», HZJZ-a, županijskih zavoda te niza drugih ustanova. Cilj istraživanja bio je pružiti sveobuhvatne podatke o zdravlju stanovnistva Hrvatske, ukljucujuci pristup i koristenje zdravstvene zastite, zdravstveni status te odrednice zdravlja (pusenje, fizicka aktivnost, prehrana, alkohol)  s posebnim naglaskom na kardiovaskularne bolesti.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.137
Threshold uncertainty score0.272

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0050.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0440.025

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 head0.024
GPT teacher head0.290
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), 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
Published2010
Admission routes1
Has abstractyes

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