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Precisión de las referencias bibliográficas de los Trabajos de Fin de Grado en Enfermería

2021· article· es· W3168495734 on OpenAlexaboutno aff
José Luis Llopis Agelán, Óliver Martín Martín, José Manuel Estrada Lorenzo, Ramón del Gallego Lastra

Bibliographic record

VenueMetas de Enfermería · 2021
Typearticle
Languagees
FieldHealth Professions
TopicHealth and Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhysicsPhilosophy

Abstract

fetched live from OpenAlex

Objective: to identify the quality of the bibliography used by students in their 4th year of the Nursing Degree at the School of Nursing, Physiotherapy and Chiropody of the Universidad Complutense de Madrid. Method: the study was conducted through the selection and evaluation of information sources and references from journal articles in 26 Final Degree Projects (FDPs), in order to determine their conformity with the Vancouver Standards, because this is the quotation system more widely used in Health Sciences publications, and recommended by the professors responsible for education and follow-up of FDP groups. Results: out of 957 references in total, there was a selection of 604 (63.11%) journal articles, and 1.545 errors (2.55 per reference) were detected and classified. The group of those with the best scores presented 17.05% of correct references, vs. 9.13% for the group with the worst score. Conclusions: low accuracy in references was found in both groups. However, the projects with higher scores provided more references, higher use of scientific journals, higher agreement with Vancouver Standards, and lower number of errors.

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 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)0.009
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.096
GPT teacher head0.483
Teacher spread0.386 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

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