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Record W1919588364 · doi:10.1111/vco.12121

Hypofractionated radiation therapy for the treatment of microscopic canine soft tissue sarcoma

2014· article· en· W1919588364 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

VenueVeterinary and Comparative Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsUniversity of Guelph
FundersUniversity of Queensland
KeywordsSoft tissueRadiation therapySoft tissue sarcomaSarcomaMedicineRadiologyPathology

Abstract

fetched live from OpenAlex

Soft tissue sarcomas (STSs) are locally invasive and surgery with or without radiation therapy is the current standard of care in dogs. Typical protocols for treating incompletely excised STSs involve curative intent radiation with total dose in excess of 50 Gy. Forty-eight dogs with histologically confirmed incomplete or closely excised STSs were treated with a hypofractionated protocol that is typically reserved for palliative radiation therapy (RT) (6-8 Gy/weekly fractions to a total dose of 24-32 Gy). Ten dogs (21%) developed local recurrence, 11 dogs (23%) developed metastasis, and 3 dogs developed both (included in each group). The median progression free survival was 698 days. The local failure-free probability at 1 and 3 years was 81 and 73%. The 1 and 3 years tumour-specific overall survival was 81 and 61%. Long-term local tumour control was achieved in the majority of dogs. This protocol is reasonable to prescribe in older patients or when financial limitations exist.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score0.358

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)0.0000.000

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 head0.150
GPT teacher head0.444
Teacher spread0.294 · 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