MétaCan
Menu
Back to cohort
Record W4393349184 · doi:10.1016/j.tipsro.2024.100246

Evaluation of RTT education – Is it fit for the present: A report on the ESTRO radiation therapist workshop

2024· article· en· W4393349184 on OpenAlexaff
Mikki Campbell, Aidan Leong, Philipp Scherer

Bibliographic record

VenueTechnical Innovations & Patient Support in Radiation Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRadiation TherapistMedical educationHealth professionalsKey (lock)PsychologyMedicineHealth careMedical physicsComputer sciencePolitical scienceSurgeryRadiation therapy

Abstract

fetched live from OpenAlex

Education is key in preparing healthcare professionals for the current and future needs of the clinical environment. Hence, ESTRO facilitated a workshop, with a track focusing on radiation therapists' (RTT) education and whether it is fit for the current demands of RTTs. An international group of participants with academic and clinical backgrounds discussed the current situation in their respective working environments, evaluated the challenges in RTT education, and highlighted opportunities and possible solutions to meet current and future needs. Key outcomes highlighted the importance of strengthening collaboration between clinical and academic staff.

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)0.073
metaresearch head score (Gemma)0.103
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.388

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0730.103
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0050.003
Open science0.0030.012
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.095
GPT teacher head0.491
Teacher spread0.397 · 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 designQualitative
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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueTechnical Innovations & Patient Support in Radiation OncologySame topicAdvances in Oncology and RadiotherapyFrench-language works237,207