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The power of altmetrics on a CV

2013· article· en· 86 citations· W2051771537 on OpenAlex· 10.1002/bult.2013.1720390405

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

gemmalow
Categories: Metaresearch, Bibliometrics
Study design: Observational
Domain: Evaluation
Genre: Empirical
About the Canadian research system: no
About a Canadian topic: no
gptmedium
Categories: Bibliometrics, Metaresearch
Study design: Not applicable
Domain: Evaluation
Genre: Commentary
About the Canadian research system: no
About a Canadian topic: no

Full frame distilled prediction

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.

Candidate categories
Metaresearch, Bibliometrics, Science and technology studies
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Not applicableConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.754
Threshold uncertainty score
0.997
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.043
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.119
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.126
GPT teacher head0.446
Teacher spread
0.320 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Abstract Editor's Summary Alternative metrics demonstrate the value and influence of scholars' work apart from traditional citation counts and can enhance the impact of a CV. Altmetrics provide additional, supplementary information and can balance misleading metrics tied to particular journals. More timely than traditional metrics, altmetrics quickly reveal the impact of recent work and add authority to different types of scholarly products not captured as articles. Altmetrics can capture social media references that escape traditional metrics and reflect public engagement prompted by scholarly writing. The availability of altmetrics expands publishing opportunities to include new venues and stimulates innovative strategies for evaluating research. When included in a CV altmetrics must be accurate, clear and meaningful.

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.

The record

Venue
Bulletin of the American Society for Information Science and Technology
Topic
scientometrics and bibliometrics research
Field
Decision Sciences
Canadian institutions
ImpactOpenAlex
Funders
not available
Keywords
AltmetricsCitationSocial mediaComputer scienceData scienceWorld Wide Web
Has abstract in OpenAlex
yes