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Record W2381289262

The Data Transaction between SQL Server Database and Oracle Database Based on ADO.NET

2009· article· en· W2381289262 on OpenAlexvenueno aff
Kaiyan Lin

Bibliographic record

VenueMicrocomputer applications · 2009
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Computational Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceDatabaseStored procedureDatabase transactionData Transformation ServicesAutocommitOracleOracle databaseDatabase serverUser-defined functionPL/SQLSQLTransaction logDatabase tuningOpen Database ConnectivityViewLog shippingDatabase designApplication serverQuery by ExampleWorld Wide WebInternet Authentication ServiceProgramming language
DOInot available

Abstract

fetched live from OpenAlex

SQL SERVER and ORACLE are very important databases,and they are widely used.Sometimes for the specific function,the data of these two kind of database need to interact.Because the existing transmission methods are quite complicated,and easy to have problems which are difficult to solve,how to use the convenient interactive surface realize data remote real-time transmissions in these two kinds of database? This is the key point of this article,which use the ADO.NET to solve the problem.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.014
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.008

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 head0.031
GPT teacher head0.308
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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
Published2009
Admission routes1
Has abstractyes

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