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Sistema de informação como ferramenta de cálculo e gestão de custos em laboratórios de análises clínicas

2006· article· pt· W1963511515 on OpenAlexaff
Kátia Cristina Ugolini Mugnol, Marcos Bosi Ferraz

Bibliographic record

VenueJornal Brasileiro de Patologia e Medicina Laboratorial · 2006
Typearticle
Languagept
FieldSocial Sciences
TopicPublic Health in Brazil
Canadian institutionsMcMaster University
Fundersnot available
KeywordsComputer scienceHumanitiesArt

Abstract

fetched live from OpenAlex

O laboratório clínico, munido de um sistema de informática que costumeiramente operacionaliza suas rotinas e atua como um importante arquivo de dados e informações, pode utilizar-se deste como uma ferramenta que seria de grande utilidade para o cálculo e a gestão do custo real dos exames e demais procedimentos que realiza. Os sistemas implementados no momento, entretanto, segundo os dados obtidos junto a nove laboratórios situados na cidade de São Paulo, são tidos por seus usuários como inadequados a esta finalidade. As opiniões a respeito foram as mesmas, independentemente do tempo em que o sistema encontra-se em operação, de sua procedência, do porte do laboratório, do tipo de atendimento que pratica, de sua situação econômico-financeira, de seu grau de automação, da formação profissional dos gestores e dos recursos que têm disponíveis.

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)0.012
metaresearch head score (Gemma)0.032
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 score0.015
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.032
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.008
Science and technology studies0.0020.002
Scholarly communication0.0110.006
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.005

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 head0.033
GPT teacher head0.358
Teacher spread0.325 · 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

Citations15
Published2006
Admission routes1
Has abstractyes

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