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Record W6950138879 · doi:10.5281/zenodo.3554007

Islandora 8 and Beyond

2019· article· en· W6950138879 on OpenAlexafffund

Bibliographic record

VenueFigshare · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsIsland Health
FundersSimon Fraser UniversityUniversity of LimerickYork UniversityMcMaster University
KeywordsSession (web analytics)Focus (optics)Point (geometry)Front (military)User interfaceInterface (matter)

Abstract

fetched live from OpenAlex

Islandora 8.x (know during development as Islandora CLAW) pairs the latest in Fedora development with a Drupal 8 front end. A major re-architecting of the previous version of Islandora, 8.x strives to improve on Islandora's long history by taking the best from its components and letting those parts do what they do best, for an experience that is more Drupal to the site builder and end user, and more Fedora in its storage. This session will delve into the details of the first full release of Islandora's Drupal 8 - Fedora 5 pairing, with a focus on migration tools, user interface and user control, a look a pilot projects and production installations, and a roadmap for where development will go next. The point of view will be 'lighty' technical, but still accessible to a general audience.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.416
Threshold uncertainty score0.832

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0060.006
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.4160.252

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 head0.020
GPT teacher head0.228
Teacher spread0.208 · 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 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

Citations0
Published2019
Admission routes2
Has abstractyes

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