MétaCan
Menu
Back to cohort
Record W2643025302 · doi:10.5539/ass.v13n7p107

Solutions to the Advancement of Stem Cell Research

2017· article· en· W2643025302 on OpenAlexvenueno aff
Sharon Huang, Erick Ceasar Huang, Chao Huang

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsStem cellInstitutionEngineering ethicsGuidelinePolitical scienceBiologyEngineeringLaw

Abstract

fetched live from OpenAlex

Stem cell research is a developing field of research that is both promising and exciting. Although research has greatly furthered scientists’ knowledge of pathological diseases, stem cell research is not unmet with controversy. These oppositions stall the advancement of stem cell therapy and its potential to cure or save millions of people’s lives, an obstacle that should be overcome for the benefit of many. Thus, to get rid of the obstacles that prohibit the advancement of stem cell research, the public should be taught the basics of stem cell research through federal funded advertisements, a research institution gathering scientist worldwide should be established outside of the US with the goal of primarily conducting stem cell research, wherever the institution is established, funding for research should not be limited to governmental funding, and finally, an international guideline for stem cell research should be established.

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)0.072
metaresearch head score (Gemma)0.085
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.072
Threshold uncertainty score0.381

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0720.085
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0030.002
Science and technology studies0.0090.028
Scholarly communication0.0130.021
Open science0.0040.016
Research integrity0.0320.045
Insufficient payload (model declined to judge)0.0190.010

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 head0.149
GPT teacher head0.457
Teacher spread0.308 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAsian Social ScienceSame topicBiomedical Ethics and RegulationFrench-language works237,207