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Record W7057700326

La Teleriabilitazione durante la pandemia da COVID-19: un’indagine dell’Ontario Physiotherapy Association delinea vantaggi e criticita

2021· article· it· W7057700326 on OpenAlexaboutno aff

Bibliographic record

VenueCineca Institutional Research Information System (Tor Vergata University) · 2021
Typearticle
Languageit
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsPublic healthMedical careNursing careMedical treatment
DOInot available

Abstract

fetched live from OpenAlex

Il governo dell’Ontario considera prioritaria l’integrazione della assistenza virtuale, per consentire una maggiore accessibilità alle cure da parte di utenti, spesso penalizzati da barriere sociodemografiche. A partire dal 27 aprile 2020 per 3 settimane, è stato condotto in Ontario un sondaggio intervistando 365 soggetti durante la pandemia Covid-19, per valutare l’esperienza maturata dai fisioterapisti con la Teleriabilitazione. Sono emersi vantaggi (continuità di cure, contenimento di costi e spostamenti da parte dei pazienti e criticità (insostituibilità della modalità in presenza per valutazioni o terapie manuali, esigenza di una adeguata alfabetizzazione digitale, scarsa disponibilità di adeguamento delle polizze assicurative). In conclusione, ribadita l’insostituibilità della modalità “in presenza” soprattutto per quel che concerne alcune procedure, la Teleriabilitazione si candida come una modalità utile a ridurre il peso sulle strutture ospedaliere, garantire continuità terapeutica, per la sua capacità di enfatizzare l’apprendimento, lo spirito cooperativo e la partecipazione attiva e consapevole del paziente.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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: none
Teacher disagreement score0.853
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0280.001

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 head0.032
GPT teacher head0.310
Teacher spread0.278 · 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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCineca Institutional Research Information System (Tor Vergata University)Same topicMagnetic confinement fusion researchFrench-language works237,207