MétaCan
Menu
Back to cohort
Record W2339356764 · doi:10.1145/1862413.1862416

Intrinsic dimensionality

2010· article· en· W2339356764 on OpenAlexaff
Vladimir Pestov

Bibliographic record

VenueSIGSPATIAL Special · 2010
Typearticle
Languageen
FieldComputer Science
TopicData Management and Algorithms
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCurse of dimensionalitySearch engine indexingSimilarity (geometry)Computer scienceInformation retrievalWorkloadGauge (firearms)Data miningTheoretical computer scienceArtificial intelligenceGeography

Abstract

fetched live from OpenAlex

Nature of the concept . Intrinsic dimensionality of data does not refer to a single well-defined parameter, but rather a diverse family of parameters associated to a given similarity workload (X, d , U) and allowing to gauge the performance of various indexing schemes for similarity-based information retrieval.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.866
Threshold uncertainty score0.815

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 communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.222
Teacher spread0.215 · 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.

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

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

Citations6
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueSIGSPATIAL SpecialSame topicData Management and AlgorithmsFrench-language works237,207