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Record W2003529426 · doi:10.1016/j.rpor.2012.08.001

Smartphones and tablets: Reshaping radiation oncologists’ lives

2012· review· en· W2003529426 on OpenAlexaff
Alfonso Gómez‐Iturriaga, Pedro Bilbao, F. Casquero, Jon Cacicedo, Juanita Crook

Bibliographic record

VenueReports of Practical Oncology & Radiotherapy · 2012
Typereview
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsRadiation oncologyPower pointMobile devicePoint of careMedicineComputer scienceMedical physicsWorld Wide WebMultimediaRadiation therapyInternal medicinePsychologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Smartphones and tablets are new handheld devices always connected to an information source and capable of providing instant updates, they allow doctors to access the most updated information and provide decision support at the point of care. AIM: The practice of radiation oncology has always been a discipline that relies on advanced technology. Smartphones provide substantial processing power, incorporating innovative user interfaces and applications. MATERIALS AND METHODS: The most popular smartphone and tablet app stores were searched for "radiation oncology" and "oncology" related apps. A web search was also performed searching for smartphones, tablets, oncology, radiology and radiation oncology. RESULTS: Smartphones and tablets allow rapid access to information in the form of podcasts, apps, protocols, reference texts, recent research and more. CONCLUSION: With the rapidly changing advances in radiation oncology, the trend toward accessing resources via smartphones and tablets will only increase, future will show if this technology will improve clinical 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 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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.002
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 head0.199
GPT teacher head0.569
Teacher spread0.370 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2012
Admission routes1
Has abstractyes

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