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Record W2620270711 · doi:10.17613/m6965w

Metadata Schema for Modernist Networks

2014· article· en· W2620270711 on OpenAlexaboutno aff
Pamela L. Caughie

Bibliographic record

VenueHumanities Commons CORE (Modern Language Association / Columbia University) · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsnot available
Fundersnot available
KeywordsMetadataComputer scienceWorld Wide WebSchema (genetic algorithms)Information retrievalDatabase

Abstract

fetched live from OpenAlex

Loyola University Chicago will host a workshop for 16 participants in digital modernist projects in the U.S., Canada, and abroad which will result in the launching of ModNets as the most recent "node" in the Advanced Research Consortium (ARC). ModNets, a federation of digital projects in the field of modernist studies, faces unique challenges as it joins the ARC organization: we will address issues specific to the field of modernist studies, particularly the metadata needs for new media, such as film and phonography. The purpose of this workshop, which will include project directors, ModNets and ARC leaders, and metadata analysts, is to review ARC's RDF (metadata) vocabulary in the light of modernist scholarship and enhance it to meet the particular needs of modernist artifacts. The outcome will be a list of proposed changes to the existing ARC vocabularies and a working set of RDF documents for two existing projects.

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 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)0.009
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.991
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0040.003
Scholarly communication0.0090.018
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0120.006

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 head0.046
GPT teacher head0.208
Teacher spread0.162 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations0
Published2014
Admission routes1
Has abstractyes

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