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Record W145683412 · doi:10.1017/cbo9780511545566

The Cambridge Textbook of Bioethics

2008· book· en· W145683412 on OpenAlexaff
Peter Singer

Bibliographic record

VenueCambridge University Press eBooks · 2008
Typebook
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBioethicsEngineering ethicsHealth careClinical EthicsEthical issuesResource (disambiguation)Political scienceSociologyMedicineManagement scienceLawEngineeringComputer science

Abstract

fetched live from OpenAlex

Medicine and health care generate many bioethical problems and dilemmas that are of great academic, professional and public interest. This comprehensive resource is designed as a succinct yet authoritative text and reference for clinicians, bioethicists, and advanced students seeking a better understanding of ethics problems in the clinical setting. Each chapter illustrates an ethical problem that might be encountered in everyday practice; defines the concepts at issue; examines their implications from the perspectives of ethics, law and policy; and then provides a practical resolution. There are 10 key sections presenting the most vital topics and clinically relevant areas of modern bioethics. International, interdisciplinary authorship and cross-cultural orientation ensure suitability for a worldwide audience. This book will assist all clinicians in making well-reasoned and defensible decisions by developing their awareness of ethical considerations and teaching the analytical skills to deal with them effectively.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.057
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.003
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0570.048

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 head0.112
GPT teacher head0.380
Teacher spread0.268 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations92
Published2008
Admission routes1
Has abstractyes

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