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Record W2886724482 · doi:10.3233/978-1-61499-872-3-82

Building Capacity in Student and Emerging Nursing Informatics Professionals Through Participation in an International Community of Practice

2018· article· en· W2886724482 on OpenAlexaff
Lorraine J. Block, Laura‐Maria Peltonen, Charlene Ronquillo, Adrienne Lewis, Raji Nibber, Lisiane Pruinelli, Maxim Topaz

Bibliographic record

VenueStudies in health technology and informatics · 2018
Typearticle
Languageen
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
Fundersnot available
KeywordsInformaticsConstruct (python library)Health informaticsCommunity of practiceWork (physics)Medical educationNursingCapacity buildingHealth Administration InformaticsNursing practiceMedicineKnowledge managementSociologyPolitical sciencePedagogyComputer scienceEngineeringPublic health

Abstract

fetched live from OpenAlex

In nursing, a community of practice have been recognized as an important construct to build capacity and support knowledge dissemination activities. The purpose of this poster is to use a community of practice framework to describe the collaborative work of an international nursing informatics, graduate student and emerging professional group.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.113
GPT teacher head0.525
Teacher spread0.412 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2018
Admission routes1
Has abstractyes

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