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Record W4410202520 · doi:10.7202/1117883ar

Ending the Journey of Suffering

2025· article· en· W4410202520 on OpenAlexvenueno aff
Ohad Avny, Batya Grin

Bibliographic record

VenueCanadian Journal of Bioethics · 2025
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The relationship between a family physician and their patients often spans many years. The primary care physician guides the patient through medical procedures and complicated decisions. Even if the physician is not the doctor making all the decisions or tailoring the treatment plan, they are often viewed by the patient as the case manager. The importance of this role is particularly evident in the geriatric population, where the challenge lies in balancing the benefits of treating complex diseases against the potential impact on the patient’s quality of life. The physician’s ability to navigate such complex issues stems not only from their professional capabilities but also from the personal relationship between them and the patient. While friendship that tends to develop over the years between a doctor and their patient can often aid the doctor in such decision-making process, occasionally such a relationship can be a pitfall. A doctor-patient relationship grounded in compassion optimizes the decision-making process to better meet the patient’s needs. That being said, it is also understood that crossing the bounds of the traditional doctor-patient relationship can present significant moral dilemmas. This story illustrates the relationship between a family physician and an elderly patient that spans over two decades. Their friendship, partially due to a prior acquaintance, influences many of their interactions, culminating in the patient’s tragic death. This text explores the sometimes-conflicting obligations of friendship versus professionalism and the ethical dilemma in of those intersecting responsibilities.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.271
GPT teacher head0.467
Teacher spread0.196 · 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 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

Explore more

Same venueCanadian Journal of BioethicsSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207