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Record W7064873858

Creating for and with Patients – How (pre-)clinical scientists transform into agents of patient involvement – or not

2025· article· en· W7064873858 on OpenAlexaff

Bibliographic record

VenueVU Research Portal · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsAthena Sustainable Materials Institute
Fundersnot available
KeywordsTransformative learningCornerstoneLiminalityWork (physics)Space (punctuation)EthnographyTransformational leadership
DOInot available

Abstract

fetched live from OpenAlex

Patient-centeredness through patient involvement (PI) is a cornerstone of the Dutch health system, advocating for inclusive decision-making, and a holistic approach to patient well-being. This idea(l) is enacted in various research projects, such as CIRCULAR – a massive research endeavor focusing on the molecular pathology of, and innovative solutions for atrial fibrillation. However, the question arises, how consortium researchers, who operate in pre-clinical laboratory settings, engage with this concept and the professed “bridging” between the academic research space and the practical patient space. How is this gap to be understood? On what terms is a transformation towards PI possible? And could a liminal lens help to make sense of the bridging?<br/><br/>As observed in prior research and preliminary ethnographic fieldwork, pre-clinical researchers struggle with the concept of PI and ways to implement it in their work. Based on personal, behavioural and environmental factors of individual researchers, different experiences and needs co-exist and call for attention if “meaningful PI” is to be realised. Existing tools nowadays only partially address those needs and experiences. Hence, receiving additional support in navigating the research system from PI scholars seems to be still highly important.<br/><br/>Taking this line of inquiry beyond the remit of ethnography, I intend to conduct a training/reflection series on PI for consortium members. In the panel, I invite participants to creatively engage in a discussion on the planned work and the question, of whether and how this work could become transformative for (pre-)clinical researchers.<br/>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.054
GPT teacher head0.403
Teacher spread0.349 · 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.

Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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