MétaCan
Menu
Back to cohort

Alberti, Rafael (1902–1999)

2018· book-chapter· en· W4243656744 on OpenAlexaff
Silvia Colás Cardona

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicMedicine and Dermatology Studies History
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPoetryArtPaintingArt historyResidencePerformance artPublishingHumanitiesHistoryLiteratureSociologyDemography

Abstract

fetched live from OpenAlex

Born in Cadiz, Andalusia, and a member of what is known as the Generation of ’27, Rafael Alberti started his career as an avant-garde painter. He began to paint when his family moved to Madrid in 1917, and later in his life, he admitted to thinking of himself as a painter before a poet. He started writing poetry in 1920, publishing some of his early works in the ultraista literary review Horizontes. His first book of poems, Marinero en tierra [Sailor in Land], won the prestigious Premio Nacional de Literatura [National Prize for Literature] in 1925. Soon would follow La amante [The mistress] in 1926 and El alba del alhelí [Dawn of the Wallflower], published in 1927. All three of these works were inspired by neo-popularismo, one of the various literary trends that influenced the Generation of ’27. The arrival of Alberti at the Residencia de Estudiantes [Student Residence] in 1924 marks a crucial moment in his life; it was at the Residencia that he met most of the members that would later form the Generation of ’27: Federico García Lorca, Salvador Dalí, Luis Buñuel, Jorge Guillén, Gerardo Diego, Pedro Salinas, Vicente Aleixandre and Dámaso Alonso, among others.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.041
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0290.016

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 head0.028
GPT teacher head0.260
Teacher spread0.232 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicMedicine and Dermatology Studies HistoryFrench-language works237,207