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Record W597814853

Collaboration between UK universities : a machine-learning based webometric analysis

2014· dissertation· en· W597814853 on OpenAlex
Patrick Kenekayoro

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWolverhampton Intellectual Repository and E-Theses (University of Wolverhampton) · 2014
Typedissertation
Languageen
FieldComputer Science
TopicWeb visibility and informetrics
Canadian institutionsnot available
FundersMenzies Centre for Australian Studies, King's College London, University of LondonAston UniversityLondon Metropolitan UniversityLiverpool John Moores UniversityUniversity of SurreyUniversity of StirlingUlster UniversityUniversity of WestminsterUniversity of HertfordshireEdinburgh Napier UniversityLondon South Bank UniversityBangor UniversityUniversity of BristolUniversity of AberdeenLoughborough UniversityUniversity of BirminghamBath Spa UniversityUniversity of SussexUniversity of LeedsHarper Adams UniversityNewcastle UniversityUniversity of St AndrewsManchester Metropolitan UniversityUniversity College LondonUniversity of SouthamptonUniversity of East AngliaQueen Mary University of LondonTrent UniversityUniversity of BradfordUniversity of BedfordshireRobert Gordon UniversityUniversity of ExeterOxford Brookes UniversityKingston UniversityNottingham Trent UniversityQueen Margaret UniversityUniversity of WolverhamptonUniversity of GloucestershireDurham UniversityAbertay UniversityUniversity of BrightonUniversity of GlasgowUniversity of East LondonLiverpool Hope UniversityImperial College LondonUniversity of DerbyUniversity of West LondonUniversity of NorthamptonDe Montfort UniversityUniversity of PortsmouthUniversity of LeicesterUniversity of ReadingGlasgow Caledonian UniversityUniversity of GreenwichUniversity of Salford ManchesterUniversity of DundeeUniversity of WorcesterSwansea UniversityCanterbury Christ Church UniversityHeriot-Watt UniversityUniversity of BathUniversity of OxfordCoventry UniversityUniversity of WarwickAberystwyth UniversitySheffield Hallam UniversityBirmingham City UniversityUniversity of CambridgeBournemouth University
KeywordsHyperlinkWebometricsWeb miningComputer scienceWorld Wide WebTable of contentsWeb pageInformation retrievalLink analysisTable (database)Filter (signal processing)Data mining
DOInot available

Abstract

fetched live from OpenAlex

Collaboration is essential for some types of research, which is why some agencies include collaboration among the requirements for funding research projects.Studying collaborative relationships is important because analyses of collaboration networks can give insights into knowledge based innovation systems, the roles that different organisations play in a research field and the relationships between scientific disciplines.Co-authored publication data is widely used to investigate collaboration between organisations, but this data is not free and thus may not be accessible for some researchers.Hyperlinks have some similarities with Table of Contents

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.007
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.213
Teacher spread0.204 · 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