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Record W6963035548 · doi:10.17605/osf.io/2ca7g

PATIENT SAFETY IN MAJOR ONCOLOGICAL EMERGENCIES: SCOPING REVIEW

2023· other· en· W6963035548 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOpen Science Framework · 2023
Typeother
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsnot available
Fundersnot available
KeywordsGrey literaturePatient safetyHealth careMEDLINEContext (archaeology)Latin AmericansSystematic reviewInclusion (mineral)

Abstract

fetched live from OpenAlex

PROTOCOL - SCOPING REVIEW PATIENT SAFETY IN MAJOR ONCOLOGICAL EMERGENCIES: SCOPING REVIEW Objective: Identify and synthesize scientific evidence on patient safety in major oncological emergencies. Question wording P (Population) – cancer patient C (Concept) – patient safety C (Context) – nurse care during major oncological emergencies What scientific evidence, in the context of nursing care in major oncological emergencies, is available to ensure patient safety? Inclusion criteria Will be included: studies published in full in English, Spanish and Portuguese; dealing with patient safety in oncological emergencies, published from 2013 to date (Ordinance No. 874/GM/MS, of May 16, 2013: National Policy for Cancer Prevention and Control in the Health Care Network) Health of People with Chronic Diseases within the Unified Health System (SUS). Exclusion criteria Will be excluded: single case studies, editorials, experience reports, annals of events, theoretical essays, narrative literature review. Data collect Data base: - Medline via the National Library of Medicine and National Institutes of Health (PubMed); - Latin American and Caribbean Literature in Health Sciences (LILACS), - SCOPUS; - Web of Science; - Base; - Cochrane Library. Gray literature search: - CAPES Theses and Dissertations Catalog - DART-Europe E-Theses Portal - Electronic Theses Online Service (EThOS) - Open Access Scientific Repository of Portugal (RCAAP) - National ETD Portal - Theses Canada - Latin American Thesis Portal - World Cat Dissertations and Theses • Identification of descriptors and keywords Descriptors and keywords used in studies that address the topic of interest from the combination of MeSH identified for the research mneumonic: (Acute tumor lysis syndrome OR Metabolic Diseases OR Syndrome of inappropriate secretion of antidiuretic hormone OR Hydroelectrolytic disorders OR Diabetes insipidus OR Malignant bowel obstruction OR Superior Vena Cava Syndrome OR Superior Mediastinal Syndrome OR Leukocytosis OR Chemotherapy-Induced Febrile Neutropenia OR Febrile Neutropenia OR Spinal Cord Compression OR Airway Obstruction) AND (Patient Safety [Mesh] OR Risk Management [Mesh] OR Medication Errors [Mesh] ) AND (Neoplasms [Mesh] OR Oncology Nursing [Mesh] OR Oncology [Mesh]).

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)0.027
metaresearch head score (Gemma)0.039
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesOpen science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.013
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0130.011
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0180.008

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 head0.201
GPT teacher head0.493
Teacher spread0.292 · 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