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Record W4280565632 · doi:10.1111/rest.12758

Issue Information

2022· paratext· en· W4280565632 on OpenAlexfundno aff
Craig Pickett, Jenifer Cabrera, Kevin Killeen, Cecilia Muratori, Alessandra Petrina

Bibliographic record

VenueRenaissance Studies · 2022
Typeparatext
Languageen
FieldEngineering
TopicHuman auditory perception and evaluation
Canadian institutionsnot available
FundersUniversità di BolognaLiverpool John Moores UniversityUniversiteit LeidenUniversity College DublinFreie Universität BerlinUniversity of SussexUniversity of OxfordFlorida State UniversityUniversity of ExeterSociety for Renaissance StudiesYork UniversityUniversity of St AndrewsJames Madison UniversityUniversity of LeicesterUniversity of WarwickNorthwestern UniversityHarvard UniversityHelsingin YliopistoUniversity of TorontoUniversity College LondonEmory University
KeywordsCitationComputer scienceRest (music)The RenaissanceWorld Wide WebInformation retrievalHistoryArt historyMedicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.076
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0020.001
Scholarly communication0.0080.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.9240.877

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 head0.044
GPT teacher head0.318
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractno

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