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Record W4300622655 · doi:10.5281/zenodo.1295954

Surgical Management Of Canine Oral Tumors.

2018· article· en· W4300622655 on OpenAlexaboutno aff
K. Jagan Mohan Reddy, V. Gireesh Kumar, K.B.P. Raghavender

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2018
Typearticle
Languageen
FieldDentistry
TopicOral and Maxillofacial Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Five male dogs with age ranging from 5 -9 years, and different breeds viz., Labrador, St. Bernard, Spitz, GSD and Mongrel one each presented to the Department of Surgery and Radiology, CVSc, Rajendranagar, PVNR TVU with a history of difficulty in eating food, after oral examination, tumor mass in the mouth was identified, Oral radiographs did not show clear borders of the mass.Clinically and macroscopically, the mass was painful and had a nodular appearance and was reddish whitein color with varying size of length ranging from 5cm - 12cm and width ranging from 5cm ? 3cm. After surgical resection of the tumor mass, Histopathologic examination of the mass in all dogs revealed that the tumors were of malignant nature, Ameloblastoma (Laborador), Fibrous Histocytoma (St.Bernard), and others Squamous cell carcinoma. Reoccurrence of tumor growth after 30 day to 60 days was noticed. Further surgical resection was taken up to facilitate for easy passage of food while eating. Four dogs died after span of 3-4 months except one mongrel dog survived without any reoccurrence.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.984

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0310.016

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 head0.039
GPT teacher head0.279
Teacher spread0.240 · 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
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
Published2018
Admission routes1
Has abstractyes

Explore more

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