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Testing the limits of emergent behavior in MAS using learning of cooperative behavior

2006· article· en· W6301683 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

VenueEuropean Conference on Artificial Intelligence · 2006
Typearticle
Languageen
FieldComputer Science
TopicMulti-Agent Systems and Negotiation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceTest (biology)Class (philosophy)Artificial intelligenceMulti-agent systemIntelligent agentHuman–computer interaction

Abstract

fetched live from OpenAlex

Previous work has suggested that potential information in DNA secondary structure might be used by cells to define DNAase 1- and S1-sensitive chromatin structures associated with promoter and terminator regions. To test this hypothesis, supercoiled pBR322 was cotransfected into L cells. For the majority of transfected clones supercoil-induced S1-sensitive sites in pure pBR322 DNA are also S1-sensitive in L-cell nuclei. These results suggest that the potential of certain DNA sequences to form specific secondary structures in chromatin can be a dominant characteristic. A recombinant chicken beta A-globin supercoiled plasmid was reconstituted in vitro with histones. The reconstituted chromatin also retained the ability to form S1-sensitive sites. Evidence suggests that DNA sequences capable of forming S1-sensitive sites in supercoiled plasmids may bind nucleosomes poorly after reconstitution with histones.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.250
GPT teacher head0.346
Teacher spread0.095 · 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