MétaCan
Menu
Back to cohort
Record W2080670657 · doi:10.1002/spe.686

Fast dynamic casting

2005· article· en· W2080670657 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

VenueSoftware Practice and Experience · 2005
Typearticle
Languageen
FieldComputer Science
TopicSoftware Testing and Debugging Techniques
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsPointer (user interface)C dynamic memory allocationComputer scienceModuloInteger (computer science)Class (philosophy)ArithmeticPredictabilityBase (topology)Theoretical computer scienceAlgorithmProgramming languageDiscrete mathematicsMathematicsArtificial intelligenceMemory management

Abstract

fetched live from OpenAlex

Abstract We describe a scheme for implementing dynamic casts suitable for systems where the performance and predictability of performance is essential. A dynamic cast from a base class to a derived class in an object‐oriented language can be performed quickly by having the linker assign an integer type ID to each class. A simple integer arithmetic operation verifies whether the cast is legal at run time. The type ID scheme presented uses the modulo function to check that one class derives from another. A 64‐bit type ID is sufficient to handle class hierarchies of large size at least nine levels of derivation deep. We also discuss the pointer adjustments required for a C++ dynamic_cast. All examples will be drawn from the C++ language. Copyright © 2005 John Wiley & Sons, Ltd.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.973
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.014
GPT teacher head0.304
Teacher spread0.289 · 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