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Record W4297900514 · doi:10.18063/ijb.v8i4.616

3D Bioprinting for Regenerating COVID-19-Mediated Irreversibly Damaged Lung Tissue

2022· review· en· W4297900514 on OpenAlexaff
F. Akter, Yusha Araf, Salman Khan Promon, Jingbo Zhai, Chunfu Zheng

Bibliographic record

VenueInternational Journal of Bioprinting · 2022
Typereview
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLungPneumoniaMedicineRespiratory systemRespiratory failureRespiratory distressCoronavirus disease 2019 (COVID-19)Diffuse alveolar damageCoronavirusDiseaseIntensive care medicineImmunologyPathologyBioinformaticsAcute respiratory distressInternal medicineBiologySurgeryInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

While the tension of COVID-19 is still increasing, patients who recovered from the infection are facing life-threatening consequences such as multiple organ failure due to the presence of angiotensin-converting enzyme 2 receptor in different organs. Among all the complications, death caused by respiratory failure is the most common because severe acute respiratory syndrome coronavirus 2 infects lung's type II epithelial, mucociliary, and goblet cells that eventually cause pneumonia and acute respiratory distress syndrome, which are responsible for the irreversible lung damage. Risk factors, such as age, comorbidities, diet, and lifestyle, are associated with disease severity. This paper reviews the potential of three-dimensional bioprinting in printing an efficient organ for replacement by evaluating the patient's condition.

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)0.005
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.002
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 head0.087
GPT teacher head0.414
Teacher spread0.327 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations11
Published2022
Admission routes1
Has abstractyes

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