MétaCan
Menu
Back to cohort
Record W2538939498 · doi:10.5703/1288284316238

Summon, EBSCO Discovery Service, and Google Scholar: Comparing Search Performance Using User Queries

2016· article· en· W2538939498 on OpenAlex
John Vickery

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
TopicInformation Retrieval and Search Behavior
Canadian institutionsPurdue Pharma (Canada)
Fundersnot available
KeywordsComputer scienceWorld Wide WebInformation retrievalService (business)Search engineBusiness

Abstract

fetched live from OpenAlex

When the NCSU Libraries initially subscribed to the Summon Discovery Service in 2009, there were few other competitors on the market and none offered an API interface that could be used to populate the “Articles” portion of our QuickSearch application (http://search.lib.ncsu.edu/). Since then, EBSCO Discovery Service (EDS) has emerged as a viable competitor. Using a random sample of actual user searches and bootstrap randomization tests (also referred to as permutation tests), the NCSU Libraries’s Web‐Scale Discovery Product Team conducted a study to compare the search performance of Summon, EDS, and Google Scholar.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.641

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 communication0.0010.008
Open science0.0000.001
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 head0.052
GPT teacher head0.277
Teacher spread0.225 · 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