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Record W2083121732 · doi:10.1100/tsw.2006.324

Limb Regeneration in Axolotl: Is It Superhealing?

2006· review· en· W2083121732 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Scientific World JOURNAL · 2006
Typereview
Languageen
FieldMedicine
TopicCorneal Surgery and Treatments
Canadian institutionsUniversité de Montréal
FundersUniversité de Montréal
KeywordsAxolotlRegeneration (biology)Regenerative medicineWound healingRegenerative processBiologyMedicineAnatomyNeuroscienceStem cellCell biologyGenetics

Abstract

fetched live from OpenAlex

The ability of axolotls to regenerate their limbs is almost legendary. In fact, urodeles such as the axolotl are the only vertebrates that can regenerate multiple structures like their limbs, jaws, tail, spinal cord, and skin (the list goes on) throughout their lives. It is therefore surprising to realize, although we have known of their regenerative potential for over 200 years, how little we understand the mechanisms behind this achievement of adult tissue morphogenesis. Many observations can be drawn between regeneration and other disciplines such as development and wound healing. In this review, we present new developments in functional analysis that will help to address the role of specific genes during the process of regeneration. We also present an analysis of the resemblance between wound healing and regeneration, and discuss whether axolotls are superhealers. A better understanding of these animals' regenerative capacity could lead to major benefits by providing regenerative medicine with directions on how to develop therapeutic approaches leading to regeneration in humans.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.794
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.115
GPT teacher head0.374
Teacher spread0.259 · 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