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Record W3018535147 · doi:10.1016/j.soncn.2020.151028

Oncology Nursing During a Pandemic: Critical Reflections in the Context of COVID-19

2020· review· en· W3018535147 on OpenAlexaff
Catherine Paterson, Bárbara Göbel, Tracy Gosselin, Pamela J. Haylock, Constantina Papadopoulou, Kim Slusser, Anna Liza Rodriguez, Edith Pituskin

Bibliographic record

VenueSeminars in Oncology Nursing · 2020
Typereview
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsUniversity of Alberta
FundersJohns Hopkins University
KeywordsPandemicCINAHLMedicineContext (archaeology)Oncology nursingMEDLINENursingCoronavirus disease 2019 (COVID-19)ScopusOncologyNurse educationInternal medicinePsychological intervention

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.028
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.028
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.050
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.003
Science and technology studies0.0030.006
Scholarly communication0.0080.012
Open science0.0020.007
Research integrity0.0120.018
Insufficient payload (model declined to judge)0.0040.001

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 head0.261
GPT teacher head0.596
Teacher spread0.335 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations117
Published2020
Admission routes1
Has abstractno

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