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Record W2901356348 · doi:10.1145/3274895.3274961

DISTIL

2018· article· en· W2901356348 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
TopicData Management and Algorithms
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsComputer scienceSPARK (programming language)Volume (thermodynamics)ThroughputDistributed computingDistributed databaseReal-time computingOperating systemWireless

Abstract

fetched live from OpenAlex

Location-based services (LBS) have become an ubiquitous technology and spatio-temporal data generated by LBS is characterized by high volume and velocity. In recent times several projects, such as GeoSpark, SpatialSpark and LocationSpark, have focused on developing spatial data systems that take advantage of the distributed in-memory data processing capability of Spark. However, most of these systems assume immutable spatial data, and they do not support high throughput location data updates that are common in LBS. On the other hand, a few HBase-based systems, such as MD-HBase, have been proposed that support data updates. However, these systems do not take advantage of any distributed in-memory query processing frameworks.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.834
Threshold uncertainty score0.999

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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

Citations10
Published2018
Admission routes1
Has abstractyes

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