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Record W7130414982 · doi:10.5281/zenodo.18675608

Shadow Souvenirs

2016· article· en· W7130414982 on OpenAlexaff
Gillian Russell, Craig Badke, Jaclyn Phillips, Derek Bruce Durand, Celia Pankhurst, Stacie Schatz, Joakim Zatko, Naitik Mehta, Delaney Lee, Devon Pianosi, Jaylen Fast, Li Zhang, Melissa Gehman, Steph Ganae, Bri Kim, Callahan Tufts, Cathy Yang, Eli Muro, Odette Hey, Roya Aghighi, Ali Alamzadeh, Chelsea Bell Eady, Andy Liao, Andy Robinson, Clayton Wadsworth

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicCrafts, Textile, and Design
Canadian institutionsEmily Carr University of Art and DesignSimon Fraser University
Fundersnot available
KeywordsShadow (psychology)CarrPaintingWindow (computing)Series (stratigraphy)

Abstract

fetched live from OpenAlex

Shadow Souvenirs is part of Emily Carr University of Art and Design's HUMN 306 - Critical Design Intensive Course. This issue is the first in a series of special supplemental course catalogues.

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 score0.389
Threshold uncertainty score0.871

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.3890.113

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 head0.058
GPT teacher head0.225
Teacher spread0.167 · 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
Published2016
Admission routes1
Has abstractyes

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