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Record W7135330178

Firm foundations

2008· other· en· W7135330178 on OpenAlexaboutno aff
David Nisbet, John Forsythe

Bibliographic record

VenueANU Open Research (Australian National University) · 2008
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRegeneration (biology)Tissue engineeringSpinal cordNerve repairHuman healthNerve cells
DOInot available

Abstract

fetched live from OpenAlex

Researchers are making efforts to use nanomaterials for the re-generation of damaged nerves in the spinal cord injury. Engineers of Monash University, the University of Melbourne, the University of Toronto, and the Mental Health Research Institute together demonstrated that cellular scaffolds can accelerate the nerve regeneration. Scaffolds are 3-dimensional engineered structures that can promote the cell growth in the human body. The guidance scaffolds are made of nanoscale polymer fibers of 100-2000 nm in diameter and can be used for post-SCI (spinal cord injury) nerve regeneration. The Therapeutic Goods Administration of Australia also approved the use of these materials for humans because of their biodegradability and non-toxicity. Engineered scaffolds provide controlled nerves regeneration and integration with the neuronal circuitry.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.378
Threshold uncertainty score0.887

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.002
Scholarly communication0.0080.004
Open science0.0020.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.3780.171

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 head0.323
GPT teacher head0.436
Teacher spread0.114 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2008
Admission routes1
Has abstractyes

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Same venueANU Open Research (Australian National University)French-language works237,207