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Record W73329660

PROCEEDINGS OF FOURTH BERKELEY CONFERENCE ON DISTRIBUTED DATA MANAGEMENT AND COMPUTER NETWORKS.

2011· article· en· W73329660 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueeScholarship (California Digital Library) · 2011
Typearticle
Languageen
FieldComputer Science
TopicDigital and Cyber Forensics
Canadian institutionsnot available
FundersSLAC National Accelerator LaboratoryUniversity of WaterlooDeutsche ForschungsgemeinschaftU.S. Department of EnergyU.S. Department of DefenseAdvanced Research Projects AgencyNational Science Foundation
KeywordsLibrary scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Data base access is increasingly important in a networking environment.Two alternative approaches can be identified: i) implementation of distributed databases presenting the user with one logical database implemented across a collection of computers or, alternatively, ii) development of network data managers providing a uniform user and program viewpoint across heterogenous DBMSs.While the first approach is the most natural extension of the concept of an individual DBMS, its utilization imposes certain requirements including the necessity for converting existing DBMSs if their data is to be supported in the distributed environment.The second approach minimiz.esor eliminates cO"lwersion problems; however, it has not yet caen shown feasible.This paper describes an ongoing research project concerned with establishing the feasibility, issues, alternatives, and a technical approach for supporting a network data manager.Although implementation has not been completed, the initial evidence is positive and suggests that network data managers may well prove either an acceptable alternative or useful intermediate stage to a distributed database.Perhaps the three key issues in ensuring user acceptance of a network data manager are: i) access controls and semantic integrity, ii) developing more sophisticated translation capabilities optimizing the allocation of the translation process among NOM and LDBMS, and iii) performance.We believe the basic issues and a reasonable approach for (i) have, been discussed in this paper.Developing a more sophisticated translation capability is of obvious importance and closely relates to the performance issue.Implementation of translators should be paralleled with research directed toward a better understanding of the nature of the translation process.Some work is beginning to appear in this area [KLUGA 78] establishing the theoretical limits of translation feasibility. Implementation StatusXNDM translation is performed on a PDp11 /45 attached to the Arpanet as are the other host computers.Tbe operating system for the PDp11 145 is UNIX [THOMK 74] and the translator' is programmed in C. To provide a more uniform interface to the translator, small support modules termed envelopes are implemented on the system on which each LDBMS resides.Basic communications support between systems and the ability to preserve meaning ,in transporting structured records between heterogeneous systems is provided by. an Experimental Network Operating System (XNOS) [KIMBS 78].Work on the XNQL translator is still in progress.The current version handles two out of the six XNQL constructs (selections of columns and rows), for the following target systems:the Multics Relational Data Store (MRDS) [HONEY 77], a relational calculus system, and the Honeywell 600/6000 Integrated Data Store (IDS) [HONEY 71], a Codasyllike system.For MRDS, the translator can handle all target data structures In general, but for IDS, target records with multiple owners and multiple members are excluded. Implementation ApproachTwo different approaches to implementing XNDM can be considered.The first distributes the implementation across the supported host systems whiie the second, which we have adopted, offloads the implementation, to the extent possible, onto a separate satellite computer.The tradeoffs between these two approaches are essentially those of evaluating the cost of supporting an additional computer versus the cost of implementing common modules on several different systems.Given the opportunity for centralized design, implementation and support.afforded by offloading and the increasingly high' cost of software, we believe that offloading is the natural approach in an evolving technology.The alternative might be appropriate for an extremely static environment.6.

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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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.642
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 studies0.0000.000
Scholarly communication0.0010.007
Open science0.0020.003
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 head0.033
GPT teacher head0.200
Teacher spread0.167 · 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