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Record W2983255247 · doi:10.1016/s0167-8140(19)33210-4

155 Successes and Barriers to the Integration of the National System for Incident Reporting-Radiation Treatment (NSIR-RT) Taxonomy into a Provincial Incident Reporting and Learning System

2019· article· en· W2983255247 on OpenAlexaff
Kathryn Moran, Helmut Hollenhorst

Bibliographic record

VenueRadiotherapy and Oncology · 2019
Typearticle
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsIncident reportMedical physicsBusinessMedicineComputer scienceComputer security

Abstract

fetched live from OpenAlex

CARO-ASM 2019V80, V50 and V20 of normal brain, comparably low homogeneity index, and acceptable ipsilateral lens dose.The VMAT plan provided the best dose homogeneity within the target volume and ipsilateral lens sparing, at the expense of increased volume of brain receiving low and moderate doses.The MEB plans provided an improvement in the DVH for the normal brain distal to the PTV and were associated with acceptable ipsilateral lens dose and homogeneity.Use of the hotspot correction feature allowed for an improvement in the dose to the ipsilateral lens and dose homogeneity among the MEB electron plans.Thus, MEB can provide benefits to complicated skin cancer cases, and should be considered against other standard options.

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)0.160
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 score0.466
Threshold uncertainty score0.927

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0730.160
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0070.004
Scholarly communication0.0120.004
Open science0.0040.009
Research integrity0.0010.004
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 head0.020
GPT teacher head0.282
Teacher spread0.263 · 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

Citations0
Published2019
Admission routes1
Has abstractno

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