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Record W7133055761

Oral mucositis and quality of life in allogeneic bone marrow transplant patients

2003· dissertation· W7133055761 on OpenAlexfundno aff
Jennifer Kushner

Bibliographic record

VenueTSpace · 2003
Typedissertation
Language
FieldMedicine
TopicOral health in cancer treatment
Canadian institutionsnot available
FundersFaculty of Dentistry, University of TorontoUniversity of Toronto
KeywordsMucositisSequelaQuality of life (healthcare)Bone marrow transplantBone marrow transplantationBone marrowPatient-reported outcome
DOInot available

Abstract

fetched live from OpenAlex

Purpose. Oral mucositis (OM) is a painful and potentially life-threatening sequela of bone marrow transplant (BMT) therapy. A patient-reported OM symptom scale (PROMS) was related to other measures of quality of life (QoL), while another scale for clinical assessment of OM using visual analogue scales (VAS-OMAS) based on a previously existing scale (OMAS) was also developed. Methods. Thirty-four patients were recruited. All questionnaires were administered over routine periods. Patients completed the PROMS and QoL questionnaires, while clinicians completed the OMAS and VAS-OMAS; one clinician using OMAS, the other using VAS-OMAS. Results. PROMS reliably measured patients' self-assessment of OM and it correlated well with QoL. The VAS-OMAS correlated well with the OMAS. Conclusions. The PROMS may be used to measure patient-based experiences with OM. The VAS-OMAS may be used interchangeably with the OMAS to assess OM and due to its simplicity of use, might even be preferred.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0030.000

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 head0.056
GPT teacher head0.401
Teacher spread0.345 · 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 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
Published2003
Admission routes1
Has abstractyes

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