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Record W2063893595 · doi:10.12775/tsb.2012.009

Nicola De Bellis: Bibliometrics And Citation Analysis, from the Science Citation Index to Cybermetrics, Lanham, Toronto, Plymouth 2009

2012· article· en· W2063893595 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueToruńskie Studia Bibliologiczne · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCompetitive and Knowledge Intelligence
Canadian institutionsnot available
Fundersnot available
KeywordsBibliometricsCitationDocumentationScience Citation IndexCitation analysisLibrary scienceIndex (typography)Citation indexScientific literatureSociologySocial scienceComputer scienceBiologyWorld Wide Web

Abstract

fetched live from OpenAlex

A review of a book that deals with bibliometrics and citation analysis. Can the methods of science be directed toward science itself? How did it happen that scientists, scientific documents, and their bibliographic links came to be regarded as mathematical variables in abstract models of scientific communication? What is the role of quantitative analyses of scientific and technical documentation in current science policy and management? Bibliometrics and Citation Analysis: From the Science Citation Index to Cybermetrics answers these questions through a comprehensive overview of theories, techniques, concepts, and applications in the interdisciplinary and steadily growing field of bibliometrics.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0180.126
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
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 head0.304
Teacher spread0.252 · 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