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The projects of local governments’ health policy programs in the area of therapeutic rehabilitation reviewed by the Agency for Health Technology Assessment and Tariff System [AOTMiT] in 2010-2017.

2017· article· en· W3006780883 on OpenAlexaboutno aff
Magdalena A. Mrożek-Gąsiorowska

Bibliographic record

VenueZdrowie Publiczne i Zarządzanie · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsAgency (philosophy)RehabilitationTariffBusinessQuarter (Canadian coin)Public relationsPolitical scienceMedicineSociologyPhysical therapyGeographySocial science

Abstract

fetched live from OpenAlex

Since 2010, the Agency for Health Technology Assessment and Tariff System (AOTMiT) has issued its opinions on health policy programs (PPZ), including therapeutic rehabilitation. Of 1,813 opinions submitted on the programs, 6.9% (126 opinions) have concerned therapeutic rehabilitation. The purpose of the study is to evaluate the proportion of and determining factors of the negative opinions presented by the AOTMiT. It has been demonstrated that nearly a quarter (23.5% in 2017) of the projects in the field of therapeutic rehabilitation are negatively assessed by the Agency, the most common reason for the negative opinion (72.4%) being inadequate project preparation. The new scheme of PPZ developed by the Agency should make it easier for local governments to design a program, thus significantly reducing the number of negative opinions on therapeutic rehabilitation programs.

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)0.040
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.875
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0400.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.334
GPT teacher head0.466
Teacher spread0.132 · 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
Published2017
Admission routes1
Has abstractyes

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