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Record W4402645111 · doi:10.21275/sr24916092846

A Critical Review on the Role of Bioprinted Tumor Models in Cancer Research

2024· review· en· W4402645111 on OpenAlexaff
Stavan Vaghela -, Dave Kaushik, N Olsen

Bibliographic record

VenueInternational Journal of Science and Research (IJSR) · 2024
Typereview
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCancerMedicineIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Tumor modeling is a contemporary method of cancer research used to build tissues that are used to mimic the progression of metastasized cancerous cells.Bioprinting techniques are becoming a more common approach to generating tissues that can be used to study the course of different cancerous pathways.Recent developments in bioprinting technology have enabled improvements in research surrounding oncology, among other fields including regenerative medicine and pharmaceutical applications.This article summarizes some of the common techniques used in bioprinting and how they can be used for current and future medical applications, with a focus on its utilization in cancer research.

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)0.031
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0310.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.004
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 head0.268
GPT teacher head0.549
Teacher spread0.282 · 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 designOther design
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

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