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Record W2773168730 · doi:10.1071/rd17375

The promise of dog cloning

2017· review· en· W2773168730 on OpenAlex
Hyun Ju Oh, Kihae Ra, Min Jung Kim, Geon A Kim, Erif Maha Nugraha Setyawan, Seok Hee Lee, Byeong Chun Lee

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

VenueReproduction Fertility and Development · 2017
Typereview
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsBC Research (Canada)
FundersRural Development AdministrationResearch Institute for Veterinary Science, College of Veterinary Medicine, Seoul National UniversitySeoul National University
KeywordsSomatic cell nuclear transferCloning (programming)Computational biologyBiologyNormalityGeneticsComputer scienceMedicineEmbryo

Abstract

fetched live from OpenAlex

Dog cloning as a concept is no longer infeasible. Starting with Snuppy, the first cloned dog in the world, somatic cell nuclear transfer (SCNT) has been continuously developed and used for diverse purposes. In this article we summarise the current method for SCNT, the normality of cloned dogs and the application of dog cloning not only for personal reasons, but also for public purposes.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.168
GPT teacher head0.399
Teacher spread0.231 · 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