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Record W2334528548 · doi:10.1097/acm.0000000000000663

Artist’s Statement

2015· article· en· W2334528548 on OpenAlexaffabout
Jessie Kang

Bibliographic record

VenueAcademic Medicine · 2015
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsDalhousie University
Fundersnot available
KeywordsFeelingPaintingStatement (logic)PassionPsychologyAestheticsMedical educationPsychoanalysisMedicineVisual artsEpistemologyArtPhilosophySocial psychology

Abstract

fetched live from OpenAlex

This painting is personal to me in different layers. Most superficially, it represents my love and passion for the human brain. I remember dissecting the cerebellum for the first time in the anatomy lab and reflecting on how beautiful the arbor vitae was. To me, the brain is a magnificent organ in its mystery and potential. We will never completely be able to understand and rationalize the brain, no matter the advances we make in science and technology.SeedlingOn a deeper level, I wanted this painting to remind myself and other medical students of our potential and capabilities. As a medical student starting my journey in the field of medicine, I often feel inadequate and lost in clinical settings. I am overwhelmed at the amount of knowledge required in the field of medicine. More often than not, I am constantly doubting myself and fearful of making mistakes because there is no possible way to know everything. This is especially true in the emergency medicine elective, where the list of differential diagnoses and procedures to become familiar with never seems to end. However, I think this painting serves as an important reminder for us to recognize that we often underestimate ourselves in what we know and are capable of doing. It helps me to recognize that we all have deep-rooted knowledge and experiences that we bring into practicing medicine. Lastly, I hope this painting serves as a reminder to other medical students that they are not alone in their feelings of inadequacy. So many before us have gone through exactly the same steps to become the knowledgeable, capable physicians they are today. We are all in the journey of medicine together. Jessie Kang Ms. Kang is a third-year medical student, Dalhousie University Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada; e-mail: [email protected]

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.055
GPT teacher head0.302
Teacher spread0.247 · 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 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
Published2015
Admission routes2
Has abstractyes

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