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Record W2465916586 · doi:10.1097/bcr.0000000000000364

Burn Rehabilitation Therapists Competency Tool—Version 2

2016· article· en· W2465916586 on OpenAlexaff
Ingrid Parry, Lisa K. Forbes, David Lorello, Lynne Benavides, Catherine Calvert, Shu-Chuan Hsu, Annick Chouinard, Matthew Godleski, Phala A. Helm, Radha Holavanahalli, Jennifer Kemp-Offenberg, Catherine E. Ruiz, Rachel Shon, Jeffrey C. Schneider, Melinda Shetler, Oscar E. Suman, Bernadette Nedelec

Bibliographic record

VenueJournal of Burn Care & Research · 2016
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsMcGill UniversityHealth Sciences Centre
Fundersnot available
KeywordsMedicineRehabilitationDelphi methodOccupational therapyBurn centerCore competencyPhysical therapyNursingMedical emergencyPoison control

Abstract

fetched live from OpenAlex

The Burn Rehabilitation Therapist Competency Tool (BRTCT) was developed in 2011 to define core knowledge and skill sets that are central to the job performance of occupational and physical therapists working with burn patients during acute hospitalization and initial rehabilitation. It was the first national effort to provide standards that burn centers could use for the training and evaluation of a BRT performance. The American Burn Association Rehabilitation Committee recently expanded the tool to include long-term rehabilitation and outpatient care in order to more fully represent all of the stages of care in which patients with burn injury receive therapy. Thirty-six burn centers contributed competencies, 17 rehabilitation experts participated in a systematic Delphi questionnaire process, and eight representatives from seven additional burn centers validated the tool. The revised BRTCT, called the BRTCT-2, includes four new practice domains and 28 new competency statements. The expanded tool provides a common framework of standards for performance for occupational and physical therapists working with patients throughout the full spectrum of burn care.

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)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.004

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 head0.036
GPT teacher head0.381
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 designNot applicable
Domainnot available
GenreMethods

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

Citations18
Published2016
Admission routes1
Has abstractyes

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