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Record W2328502190 · doi:10.7748/ns.29.34.3.s1

Whoever gets in should leave the NHS alone

2015· editorial· en· W2328502190 on OpenAlexaboutno aff
Graham Scott

Bibliographic record

VenueNursing Standard · 2015
Typeeditorial
Languageen
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsPollingQuarter (Canadian coin)RecallPoliticsGeneral electionOutcome (game theory)PsychologyPolitical scienceNursingMedicineLawComputer scienceEconomicsHistory

Abstract

fetched live from OpenAlex

With only two weeks to go until polling day, the main political parties have now all revealed their plans for the next five years. With around 1,800 nursing staff in each constituency, politicians’ ability to sway the opinions of those yet to decide how to vote could determine the general election’s outcome. Especially given that, as you may recall, a Nursing Standard poll taken before campaigning started in earnest showed that more than one quarter of our readers had not decided which party to support.

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)0.005
metaresearch head score (Gemma)0.025
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.025
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0040.004
Scholarly communication0.0110.007
Open science0.0030.002
Research integrity0.0200.038
Insufficient payload (model declined to judge)0.0220.031

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 head0.045
GPT teacher head0.370
Teacher spread0.326 · 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
GenreEditorial

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
Published2015
Admission routes1
Has abstractyes

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