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Record W2162294668 · doi:10.1145/373626.373713

The Clio project

2001· article· en· W2162294668 on OpenAlexaff
Renée J. Miller, Mauricio A. Hernández, Laura M. Haas, Ling-Ling Yan, C.-T. Ho, Ronald Fagin, Lucian Popa

Bibliographic record

VenueACM SIGMOD Record · 2001
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Database Systems and Queries
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceSet (abstract data type)Data integrationTransformation (genetics)Data scienceSoftware engineeringProgramming languageDatabase

Abstract

fetched live from OpenAlex

Clio is a system for managing and facilitating the complex tasks of heterogeneous data transformation and integration. In Clio, we have collected together a powerful set of data management techniques that have proven invaluable in tackling these difficult problems. In this paper, we present the underlying themes of our approach and present a brief case study.

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)0.011
metaresearch head score (Gemma)0.017
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.065
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.017
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0020.002
Scholarly communication0.0090.010
Open science0.0040.013
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0650.040

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 head0.032
GPT teacher head0.290
Teacher spread0.259 · 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

Citations343
Published2001
Admission routes1
Has abstractyes

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