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Record W4234752579 · doi:10.48195/jie2021-170

PLANEJAMENTO DA ASSISTÊNCIA DE ENFERMAGEM À GESTANTE EM UMA UTI COVID

2021· article· pt· W4234752579 on OpenAlex
Fabrício da Cunha Moraes, BRUNA DE OLIVEIRA JOCHIMS, Caroline Santini Rauber, EVELYNE DUARTE DE AMORIM SILVA

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnais ... Jornada Internacional de Enfermagem · 2021
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsProfessional Engineers Ontario
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Computer scienceMedicineInternal medicine

Abstract

fetched live from OpenAlex

The World Health Organization (WHO) defined 2020 as the year of nursing, but the pandemic caused by the SARSCoV-2 virus brought a huge challenge of adaptation and holistic patient care among the chaos of the world health system.Even though there is a lack of further evidence about the severity of COVID-19 for pregnant women, the WHO has classified them as a risk group.The objective of this Experience Report (ER) is to demonstrate that the Systematization of Nursing Care (SNC) can be the differential for patients in hospital treatment due to complications related to COVID-19.The experience happened in the period from 11/14/2020 to 11/23/2020, during the hospitalization of a pregnant woman 1 Relato de experiência.

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.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0040.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.081
GPT teacher head0.359
Teacher spread0.278 · 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