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Record W6996368524

Rilevazione dell'attivita di Pronto Soccorso nella Regione Abruzzo - Anno 2010

2011· book· it· W6996368524 on OpenAlexaboutno aff

Bibliographic record

VenueInstitutional Research Information System University of Ferrara (University of Ferrara) · 2011
Typebook
Languageit
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Period (music)Nova scotia
DOInot available

Abstract

fetched live from OpenAlex

La valutazione ed il miglioramento della qualità dei servizi rappresentano degli obiettivi fondamentali in qualsiasi sistema sanitario. Nella cura della salute, come in altri ambiti, ciò che non può essere misurato difficilmente può essere migliorato. La presente rilevazione, oltre a descrivere una serie di dati riguardanti l’attività svolta dalle Unità Operative (UU.OO.) di Pronto Soccorso (P.S.) della Regione Abruzzo nel corso dell’anno 2010, utilizza anche una serie di indicatori già descritti e validati nella relazione finale del Progetto Mattone “Pronto Soccorso e Sistema 118” al fine di mettere in atto un’indagine conoscitiva in merito alle prestazioni erogate all’interno dei P.S. (weblink:http://www.nsis.salute.gov.it/mattoni/documenti/MDS_MATTONI_SSN_milestone_1.2.4_Formazione_PS_v1_0.pdf) 2.

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)0.003
metaresearch head score (Gemma)0.010
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.570

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.321
GPT teacher head0.383
Teacher spread0.062 · 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
Published2011
Admission routes1
Has abstractyes

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