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Record W2298880756 · doi:10.1387/ijdb.12705668

Reverse engineering the embryo: a graduate course in developmental biology for engineering students at the University of Manitoba, Canada

2003· article· en· W2298880756 on OpenAlexaffabout
Richard Gordon, Cameron Melvin

Bibliographic record

VenueThe International Journal of Developmental Biology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBiologyProcess (computing)ComprehensionEngineering ethicsObject (grammar)Course (navigation)Graduate studentsEmbryoComponent (thermodynamics)Mathematics educationComputer scienceCell biologyEngineeringMathematicsArtificial intelligencePsychologyPhysicsPedagogy

Abstract

fetched live from OpenAlex

Our desire to educate engineers to be able to understand the component processes of embryogenesis, is driven by the notion that only when principles borrowed from mathematics, fluid mechanics, materials science, etc. are applied to classical problems in developmental biology, will sufficient comprehension be achieved to permit successful understanding and therapeutic manipulation of embryos. As it now stands, biologists seldom possess either skills or interest in those areas of endeavor. Thus, we have determined that it is easier to educate engineers in the principles of developmental biology than to help biologists deal with the complexities of engineering. We describe a graduate course that has been taken, between 1999 and 2002, by 17 engineering students. Our goal is to prepare them to reverse engineer the embryo, i.e., to look at it as an object or process whose construction, albeit self-construction, might be explicable in terms of engineering principles applied at molecular, cellular and whole embryo levels.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.021
GPT teacher head0.248
Teacher spread0.227 · 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 designBench or experimental
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

Citations11
Published2003
Admission routes2
Has abstractyes

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