MétaCan
Menu
Back to cohort
Record W2398718182 · doi:10.14236/ewic/eva2013.5

Interactively Exploring Picasso’s Multi-dimensional Creative Process in Producing Guernica

2013· article· en· W2398718182 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueElectronic workshops in computing · 2013
Typearticle
Languageen
FieldNeuroscience
TopicAesthetic Perception and Analysis
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPICASSOCreativityVisual artsRubricComputer scienceSubject (documents)ArtPsychologyMathematics educationWorld Wide Web

Abstract

fetched live from OpenAlex

Picasso’s masterpiece Guernica and his creative process that gave fruition to it, has been the subject of major debate on how the creative mind works by many art historians and more recently cognitive scientists. One reason Guernica has become the rubric for discussing the ’creative process’ is Picasso, in untypical fashion, deeply documented his short, motivated and unrelenting creative process from the day he heard about the Guernica bombing to the final large canvas with approximately seventy dated images in forty five days, leaving us with significant data to pontificate the understanding the creative mind. However, the family of Guernica sketches are not easily diagnosed, containing many themes, experimental deviations, historical references, epochs of different creative directions and much more. Many researchers have underestimated the complexity involved in Picasso’s creative tour de force. Our research creates a multi-dimensional interactive and syntax of the work, from all its intertwined thematic, milestone, experimental and creative levels with the goal of creating an interactive system that allows lay viewers and experts alike to explore the complex archive of evidence.

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.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.062
GPT teacher head0.320
Teacher spread0.258 · 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