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Record W3031149882 · doi:10.1001/amajethics.2020.482

A Permanent Lisa

2020· article· en· W3031149882 on OpenAlexaff
Mark Gilbert

Bibliographic record

VenueThe AMA Journal of Ethic · 2020
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsDalhousie University
FundersUniversity of Nebraska Medical Center
KeywordsGeology

Abstract

fetched live from OpenAlex

This article describes one collaborative arts-based research project.Portrait artist Mark Gilbert considers lessons for art and healing from one patient, Lisa.Lisa took comfort in the permanence of portraiture amidst the uncertainties of tongue cancer.Arts-Based Research The Experience of Portraiture in a Clinical Setting (EPICS) project sought to explore my artistic interactions and shared experiences with patients from the Head and Neck Cancer Clinic at the University of Nebraska Medical Center. 1 The following portraits of Lisa enable investigation of the ethical and aesthetic value of permanence in Lisa's illness and portraiture experiences.Figure 1.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.430
Threshold uncertainty score0.813

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0100.002
Scholarly communication0.0050.002
Open science0.0010.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.4300.178

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 head0.067
GPT teacher head0.343
Teacher spread0.277 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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