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Record W4381165944 · doi:10.5505/tjo.2023.4015

Frostbite and Cancer

2023· article· en· W4381165944 on OpenAlex
Ali Tafazoli

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

VenueTurkish Journal of Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsSt. Lawrence College
Fundersnot available
KeywordsFrostbiteMedicineCancerSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Frostbites can be associated with a number of acute or long-term complications. One of these chronic adversities is neoplastic disorders, arising from frostbite lesions. Because of the sparseness of the available studies in medical literature, in this narrative review, the association between frostbite and cancer was explored with more focus on real-life clinical cases. The results from database searching revealed that only a few studies have evaluated this vicious companionship. According to the studies, frostbite can be a causative factor in the initiation and development of cancerous pathologies. On the other hand, some specific neoplastic disorders have been presented as risk factors for such cold injuries. It can be concluded that thorough evaluation of frostbite cases toward the full healing and considering cancers as a risk factor for cold injuries through the diagnostic procedures can be life and cost-saving for health-care systems.

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 score0.383
Threshold uncertainty score0.301

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 head0.042
GPT teacher head0.379
Teacher spread0.336 · 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