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Record W1006627952 · doi:10.1017/cbo9780511977381.007

The Object Pattern

2011· book-chapter· en· W1006627952 on OpenAlexaff
Damian Rouson, Jim Xia, Xiaofeng Xu

Bibliographic record

VenueCambridge University Press eBooks · 2011
Typebook-chapter
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsIBM (Canada)
Fundersnot available
KeywordsSpeedupComputer scienceConsistency (knowledge bases)Parallel computingCode (set theory)SoftwareClass (philosophy)Object codeObject-oriented programmingObject (grammar)Operating systemProgramming languageCode generationSet (abstract data type)

Abstract

fetched live from OpenAlex

Large software development efforts typically require a degree of consistency across the project to ensure that each developer follows practices consistent with the critical goals of the project. In high-performance computing (HPC), for example, Amdahl's law (Chapter 1) suggests that scaling up to the tens or hundreds of thousands of processor cores available on leadership-class machines requires that every dusty corner of the code make efficient use of the available cores. Otherwise, whichever fraction of the code speeds up more slowly with increasing numbers of cores eventually determines the overall speedup of the code.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.935
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0030.001
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 head0.026
GPT teacher head0.188
Teacher spread0.162 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2011
Admission routes1
Has abstractyes

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