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Record W1520653929 · doi:10.2349/biij.3.1.e2

Initial experience in treating lung cancer with helical tomotherapy

2007· article· en· W1520653929 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiomedical Imaging and Intervention Journal · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsTomotherapyMedicineLung cancerRadiation treatment planningRadiologyNuclear medicineMedical physicsRadiation therapyScannerComputer scienceArtificial intelligenceOncology

Abstract

fetched live from OpenAlex

Helical tomotherapy is a new form of image-guided radiation therapy that combines features of a linear accelerator and a helical computed tomography (CT) scanner. Megavoltage CT (MVCT) data allow the verification and correction of patient setup on the couch by comparison and image registration with the kilovoltage CT multi-slice images used for treatment planning. An 84-year-old male patient with Stage III bulky non-small cell lung cancer was treated on a Hi-ART II tomotherapy unit. Daily MVCT imaging was useful for setup corrections and signaled the need to adapt the delivery plan when the patient's anatomy changed significantly.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.703
Threshold uncertainty score0.680

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)0.0010.000

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 head0.011
GPT teacher head0.380
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