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Record W2126223847 · doi:10.1109/mcte.2002.1175046

Genetic circuit design from an electronics perspective

2003· article· en· W2126223847 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEvolutionary Algorithms and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCircuit designLinear circuitCapacitorComputer scienceCircuit extractionDiscrete circuitElectronic circuitEquivalent circuitElectronic engineeringElectronicsElectronic circuit simulationNetwork analysisMixed-signal integrated circuitElectrical elementAmplifierElectrical engineeringEngineeringCMOSVoltage

Abstract

fetched live from OpenAlex

Synthetic genetic circuits are examined from an electronic circuit design perspective. The design of an amplifier is used to explore interactions between genetic elements used as circuit components. A stochastic simulation is developed. This is used to analyze performance in terms of elementary notions of feedback, gain and noise. Degradation reactions, analogous to leakage off circuit capacitors, are found to have considerable impact on circuit response. For the non-linear gain element used in our exemplary circuit, the selection of bias level plays an important role in determining circuit behavior.

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)0.000
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: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.463
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.022
GPT teacher head0.252
Teacher spread0.229 · 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

Quick stats

Citations5
Published2003
Admission routes1
Has abstractyes

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