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Record W2116444959 · doi:10.1109/asap.2002.1030711

Efficient conversion from binary to multi-digit multi-dimensional logarithmic number systems using arrays of range addressable look-up tables

2003· article· en· W2116444959 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
TopicNumerical Methods and Algorithms
Canadian institutionsUniversity of CalgaryUniversity of Windsor
Fundersnot available
KeywordsBinary numberLogarithmComputer scienceFloating pointRepresentation (politics)Range (aeronautics)Domain (mathematical analysis)Point (geometry)Parallel computingAlgorithmArithmeticTheoretical computer scienceComputer hardwareMathematics

Abstract

fetched live from OpenAlex

The multi-dimensional logarithmic number system (MDLNS), with similar properties to the logarithmic number system (LNS), provides more degrees of freedom than the LNS by virtue of having two orthogonal bases and the ability to use multiple digits. Unlike the LNS, there is no direct functional relationship between binary/floating point representation and the MDLNS representation. Traditionally look-up tables (LUTs) were used to move from the binary domain to the MDLNS domain. This method can be unrealistic for hardware implementation when large binary ranges or multiple digits are used. This paper introduces a range addressable technique for table look-up arrays that allows efficient conversion from binary to single or multi-digit MDLNS.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.301
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.055
GPT teacher head0.302
Teacher spread0.247 · 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

Citations12
Published2003
Admission routes1
Has abstractyes

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