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Record W2028279552 · doi:10.1155/2014/947082

Assessment of Objective Ambulation in Lower Extremity Sarcoma Patients with a Continuous Activity Monitor: Rationale and Validation

2014· article· en· W2028279552 on OpenAlexaboutno aff
Kenneth R. Gundle, Stephanie Punt, Ernest U. Conrad

Bibliographic record

VenueSarcoma · 2014
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSarcomaActivity monitorAnkleSoft tissue sarcomaPhysical therapySurgeryPopulationPhysical activityPathology

Abstract

fetched live from OpenAlex

In addition to patient reported outcome measures, accelerometers may provide useful information on the outcome of sarcoma patients treated with limb salvage. The StepWatch (SW) Activity Monitor (SAM) is a two-dimensional accelerometer worn on the ankle that records an objective measure of walking performance. The purpose of this study was to validate the SW in a cross-sectional population of adult patients with lower extremity sarcoma treated with limb salvage. The main outcome was correlation of total steps with the Toronto Extremity Salvage Score (TESS). In a sample of 29 patients, a mean of 12 days of SW data was collected per patient (range 6-16), with 2767 average total steps (S.D. 1867; range 406-7437). There was a moderate positive correlation between total steps and TESS (r = 0.56, P = 0.002). Patients with osseous tumors walked significantly less than those with soft tissue sarcoma (1882 versus 3715, P < 0.01). This study supports the validity of the SAM as an activity monitor for the objective assessment of real world physical function in sarcoma patients.

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)0.007
metaresearch head score (Gemma)0.014
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 score0.007
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.258
Teacher spread0.248 · 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

Citations11
Published2014
Admission routes1
Has abstractyes

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