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Record W1979342696 · doi:10.1177/0165551507079132

Phenomenon and manifestation of the `Author's Effect of Showcasing' (AES): a literature science study, II. Very heterogeneous documentedness of historically synchronous conference communications of a single natural science

2007· article· en· W1979342696 on OpenAlexaff
Endre Száva‐Kováts

Bibliographic record

VenueJournal of Information Science · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsLibrary of Parliament
Fundersnot available
KeywordsPhenomenonCorrectnessHomogeneousComputer scienceScientific communicationNatural phenomenonDoctrineStock (firearms)EpistemologyLibrary scienceHistoryNatural (archaeology)Political scienceMathematicsPhilosophyLaw

Abstract

fetched live from OpenAlex

The `Author's Effect of Showcasing' (AES) is the activity of publishing authors who shape by their own free will the formal reference stock of their communications, placing this stock into the showcase of science. This paper reports the results of a decisive control test of the existence of the AES, processing 1175 historically synchronous physics conference communications. Applying methods of bibliometrics and science philology, the manifestation of the AES phenomenon is demonstrated and analysed in this theoretically most homogeneous domain of scientific literature. The widely differing documentedness in the communications of conferences held on particular topics of physics, especially the great differences in the size of the formal reference stocks in all extent categories of the communications depends solely on the person of the authors. This generally extremely heterogeneous documentedness is therefore valid evidence of the existence of the effect and its effective operation in the scientific literature. The correctness of the AES doctrine, including the correctness of two additional theses, has been demonstrated.

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.

How this classification was reachedexpand

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.010
GPT teacher head0.284
Teacher spread0.274 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2007
Admission routes1
Has abstractyes

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