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Record W2154259107 · doi:10.1586/17474086.2015.995623

In the realms of future: new frontiers of ‘techno-oncology’ as a platform for global improvement in the outcomes of childhood cancer

2014· editorial· en· W2154259107 on OpenAlexaff
Ketan Kulkarni

Bibliographic record

VenueExpert Review of Hematology · 2014
Typeeditorial
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsIzaak Walton Killam Health Centre
Fundersnot available
KeywordsMedicinePaceChildhood cancerScope (computer science)Developing countryPediatric oncologyCancerOncologyEconomic growthInternal medicine

Abstract

fetched live from OpenAlex

The survival outcome of childhood cancers in developing nations has failed to keep pace with that of developed nations. Technological advances offer a unique and radical opportunity to develop programs and strategies to improve outcomes of childhood cancer globally. The novel field of 'techno-oncology' has a broad scope and the potential to phenomenally impact, revamp and model the care of pediatric cancer patients in the developing world. Many frontiers and opportunities in the area remain to be explored as well as many challenges to be surmounted.

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)0.008
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.014
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.022
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0020.004
Scholarly communication0.0070.008
Open science0.0030.002
Research integrity0.0140.032
Insufficient payload (model declined to judge)0.0050.004

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 head0.387
Teacher spread0.371 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations5
Published2014
Admission routes1
Has abstractyes

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