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Record W1973368448 · doi:10.1145/1138470.1138473

Open BEAGLE

2006· article· en· W1973368448 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

VenueACM SIGEVOlution · 2006
Typearticle
Languageen
FieldComputer Science
TopicEvolutionary Algorithms and Applications
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsComputer scienceCrossoverSoftwareEvolutionary algorithmTheoretical computer scienceEvolutionary computationVariation (astronomy)Listing (finance)Software evolutionSoftware engineeringProgramming languageSoftware systemArtificial intelligenceSoftware construction

Abstract

fetched live from OpenAlex

Numerous Evolutionary Computations (EC) software tools are now publicly available to the community - see for instance [1] and [2] for a listing of the most well known. The majority of these tools are specific to a particular EC flavor, however, only a few are truly generic EC softwares [3]. The highly diverse and adaptable nature of Evolutionary Algorithms (EA) make generic EC software tools a must-have for rapid prototyping of new approaches. As we all know, EC comprises a broad family of techniques where populations of solutions to problems are represented by some appropriate data structures (e.g. bit strings, real-valued vectors, trees, etc.) on which variation operators (e.g. mutation, crossover, etc.) are applied using iterative algorithms inspired from natural evolution. Different fitness measures can also be used, with one or several objectives, and it is possible to coevolve several species of solutions, with different species represented by possibly different data structures.

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: none
Teacher disagreement score0.796
Threshold uncertainty score0.421

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 communication0.0000.001
Open science0.0020.001
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 head0.018
GPT teacher head0.264
Teacher spread0.246 · 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