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Record W1575206630 · doi:10.5772/55795

Hyperthermia: Cancer Treatment and Beyond

2013· book-chapter· en· W1575206630 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInTech eBooks · 2013
Typebook-chapter
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversité du Québec à MontréalMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMedicineCancerIncidence (geometry)Internal medicineEsophagusLung cancerAdenocarcinomaOncologyRadiation therapyThyroid cancerBreast cancerMelanomaProstate cancerPancreasKidney cancerCancer research

Abstract

fetched live from OpenAlex

The three mainstays for cancer treatment include surgical removal of tumors, radiation therapy and chemotherapy, which have led to improved patient survival for certain types of cancer, but there is still much room for improvement. Cancer is one of the leading causes of death worldwide and accounted for 7.6 million deaths (13% of all deaths) in 2008 (World Health Organization, 2012). The 2012 Report to the Nation on the Status of Cancer indicated that there was a decrease in overall cancer mortality and incidence in the U.S.A. from 1999 to 2008, particularly for the four major cancer sites: lung, colorectum, breast and prostate [1]. However, there were increases in the incidence of other types of cancer, including those of the pancreas, kidney, thyroid and liver, as well as melanoma and adenocarcinoma of the esophagus, from 1999 to 2008.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.977
Threshold uncertainty score1.000

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 head0.015
GPT teacher head0.217
Teacher spread0.202 · 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