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Record W2901594261 · doi:10.47513/mmd.v10i2.608

Relationship Completion in Palliative Care Music Therapy: Clinical Case Research Overview and Results-Part 2

2018· article· en· W2901594261 on OpenAlexaff
Amy Clements-Cortés

Bibliographic record

VenueMusic and Medicine · 2018
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCoding (social sciences)Music therapyPsychologyQualitative researchPrimary carePalliative carePsychotherapistParticipant observationMedical educationMedicineNursingSociologyFamily medicineSocial science

Abstract

fetched live from OpenAlex

Part I 1 of this paper presented the clinical case of Bill: a participant in the research study investigating the role of relationships completion in palliative care music therapy. Part II presents a brief overview of the research study, and the results of Bill’s case (one of the four primary participants). The study sought to answer the primary question: What is the experience of a dying person engaged in a specific music therapy treatment program intended to facilitate relationship completion? The investigation was a phenomenological qualitative inquiry that included multiple data sources analysed through a process coding of the data and identifying themes.

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)0.010
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.023
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0050.004
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.701
GPT teacher head0.581
Teacher spread0.120 · 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 designCase report
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

Citations3
Published2018
Admission routes1
Has abstractyes

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