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Record W2095022763 · doi:10.1089/ten.tea.2013.0468

A Global Assessment of Stem Cell Engineering

2014· article· en· W2095022763 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.

Bibliographic record

VenueTissue Engineering Part A · 2014
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of Toronto
FundersNational Cancer InstituteNational Institute of Standards and TechnologyNational Institutes of HealthNational Science Foundation
KeywordsCommercializationEngineering managementMultinational corporationEngineeringEngineering ethicsBusinessMarketing

Abstract

fetched live from OpenAlex

Over the last 2 years a global assessment of stem cell engineering (SCE) was conducted with the sponsorship of the National Science Foundation, the National Cancer Institute at the National Institutes of Health, and the National Institute of Standards and Technology. The purpose was to gather information on the worldwide status and trends in SCE, that is, the involvement of engineers and engineering approaches in the stem cell field, both in basic research and in the translation of research into clinical applications and commercial products. The study was facilitated and managed by the World Technology Evaluation Center. The process involved site visits in both Asia and Europe, and it also included several different workshops. From this assessment, the panel concluded that there needs to be an increased role for engineers and the engineering approach. This will provide a foundation for the generation of new markets and future economic growth. To do this will require an increased investment in engineering, applied research, and commercialization as it relates to stem cell research and technology. It also will require programs that support interdisciplinary teams, new innovative mechanisms for academic-industry partnerships, and unique translational models. In addition, the global community would benefit from forming strategic partnerships between countries that can leverage existing and emerging strengths in different institutions. To implement such partnerships will require multinational grant programs with appropriate review mechanisms.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.564
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)0.0000.000

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 head0.010
GPT teacher head0.266
Teacher spread0.256 · 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