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Record W2202038458

Informed Consent to Treatment in Psychiatry

2015· article· en· W2202038458 on OpenAlexaff
Grainne E. Neilson, Gary Chaimowitz

Bibliographic record

VenuePubMed Central · 2015
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsSt. Joseph’s Healthcare HamiltonNova Scotia Hospital
Fundersnot available
KeywordsInformed consentDignityAutonomyPsychiatryPsychologyPatient rightsHealth careMedicineLawAlternative medicinePolitical science
DOInot available

Abstract

fetched live from OpenAlex

Patients have a right to be informed and actively involved in their health care. Fundamental to a person’s dignity and autonomy is the right to make decisions about their psychiatric treatment, including their right to refuse unwanted treatments, providing that the refusal is a capable one. It is important that psychiatrists have an awareness of the ethical underpinnings of consent and the legislated requirements related to consent, including precedent cases. Consent may change over time and for different conditions and circumstances. Consent must be an ongoing process.

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)0.122
metaresearch head score (Gemma)0.287
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.122
Threshold uncertainty score0.645

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1220.287
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.004
Science and technology studies0.0050.025
Scholarly communication0.0090.011
Open science0.0050.009
Research integrity0.0290.022
Insufficient payload (model declined to judge)0.0230.008

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 head0.191
GPT teacher head0.478
Teacher spread0.288 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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