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Record W7045734496

Cardiopulmonary and Cancer Rehabilitation

2022· article· en· W7045734496 on OpenAlexaboutno aff

Bibliographic record

VenueThe Mathematics Enthusiast · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationWork (physics)Test (biology)CancerCardiopulmonary resuscitationCapstone
DOInot available

Abstract

fetched live from OpenAlex

For this capstone project we are helping with the first phase of a 4-phase curricular/outreach program designed to train students (undergraduate and graduate in a peer-mentoring fashion) about professional work in Exercise Rehabilitation for Cardiopulmonary and Cancer Patients. Step 1 includes helping to develop the programmatic approach to testing students as a stand-in for clinical patients. This hands-on approach includes participating in the actual clinical equipment, procedures, and logistics used in modern clinical facilities. Because this program is being developmed in an existing laboratory space that is being repurposed as the Cardiopulmonary and Cancer Rehabilitation Laboratory, our work includes curating the procedures, reconfiguring the lab space, and developing/evolving the initial exercise and testing procedures for patient testing. Among the duties undertaken is the configuration of new equipment in the lab, mock using the equipment in simulated exercise classes, and refining the distribution of exercise ergometers to match the evolving protocols within the lab. Moreover, because this lab setting is designed to mimic clinical settings in small regional medical facilities, we are learning the best ways to utilize our small place in the basement of McGill. One specific type of assessment that we are introducing to the lab is a 6-minute-walk-test (6MWT). This assessment is used to determine certain levels of cardiovascular fitness. The 6MWT is a high-quality test for diseased patients with relatively low levels, including our potential future cancer and pulmonary patients. In the lab we will have 3 treadmills, a NuStep, an arm ergometer, rower, a stair stepped, an elliptical trainer, and 2 bike ergometers available for future patients. In addition, there is strength training equipment, and floor space available for stretching and core exercises. For a given exercise session, each patient will participate in 5 different exercise modalities, not including a structured warm-up and cool-down. All of these exercises will be performed while monitored with a state of the art ECG telemetry (radio transmitted to a central computer station), periodic blood pressure measurements, blood oxygen saturation, and a metric of an individual rate of perceived exertion (subjective feelings of effort), in addition to resting vital signs. Each exercise session is completed within a 60-minute rehabilitation time window. Finally, we have been tasked with the development of patient education materials (1-2 page handouts) on medication use, managing signs and symptoms of recurrent disease, etc. Patient materials also include large full color posters for the facility walls. Poster topics include stretching, lifestyle medicine, strength training exercises, and a scale for the rating of perceived exertion. Once the facility and initial phase of the Cardiopulmonary Rehabilitation program is designed, the lab is also going to be configured for the dual application to Cancer Rehabilitation. These dual purposes apply to rural medical settings in that many smaller cardiopulmonary rehab settings are only used for part of a 40-hour work week. Thus, with the shortage of funds for dedicated facilities, cancer patients could use the same facilities as cardiac patients, maximizing the off hours for exercise classes directed to those recovering from a cancer diagnosis. All the while we are also discussing peer-reviewed manuscripts related to these topics of exercise rehabilitation, discussing the scientific process that underpins applications of exercise physiology to clinical settings, and working on professional development topics with our peers and faculty mentor.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0810.000

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 head0.013
GPT teacher head0.268
Teacher spread0.255 · 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 teacher head, not a consensus.

Study designNot applicable
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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