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Realizing associated evolution courses: The co-evolution in the artificial world of manufacturing

2010· article· en· W28449923 on OpenAlexaff
Tarek AlGeddawy, Hoda ElMaraghy

Bibliographic record

VenueInternational Conference on Evolutionary Computation · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCollaboration in agile enterprises
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsComputer scienceManufacturing engineeringArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

This study describes the use of a set of protein-based biomaterials that allow us to explore the mechanism of cell-mediated 3-D invasion associated with peripheral nerve regeneration. Hydrogels made from poly(ethylene glycol) (PEG) conjugated extracellular matrix proteins, including fibrinogen, gelatin and albumin were compared in their ability to support the neurite extension and glial cell migration from dorsal root ganglion (DRG) as compared to PEG only hydrogel controls. The synthetic polymer in the system provides a cross-linked network with controlled mechanical properties and degradation, whereas the protein components provide the unique extracellular matrix (ECM) for controlling neuronal cell morphogenesis. A range of hydrogel compositions were found to support DRG cell outgrowth, based on the mechanical properties, density and proteolytic degradation of the matrix. The 3-D invasion and morphogenesis of newly grown neurites and glial cells in the different materials were characterized and correlated to the properties of the scaffolds. The DRG cell outgrowth was highly correlated with the density of different hydrogel compositions.

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 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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.033
GPT teacher head0.297
Teacher spread0.265 · 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 teacher head, 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

Citations2
Published2010
Admission routes1
Has abstractyes

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