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Record W3034322173 · doi:10.3989/ic.71572

Rascacielos a la italiana. Construcción de gran altura en los años cincuenta y sesenta

2020· article· es· W3034322173 on OpenAlexaboutno aff
Gianluca Capurso

Bibliographic record

VenueInformes de la Construcción · 2020
Typearticle
Languagees
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
FundersUniversità degli Studi di Roma Tor Vergata
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

En los años cincuenta y sesenta del siglo XX, mientras la ingeniería italiana recibía importantes premios internacionales, el diseño de los edificios en altura atraía la atención de los mejores arquitectos. Estos entendieron inmediatamente lo mucho que el empleo estratégico de la estructura habría podido revolucionar la ya de por sí estereotipada imagen de la torre de acero y vidrio propuesta por el Estilo Internacional, y lo convirtieron en un campo de experimentación. De esta forma Gio Ponti, Luigi Moretti y la BBPR desarrollaron extraordinarias colaboraciones con Pier Luigi Nervi y Arturo Danusso, los ingenieros más activos en el campo del diseño de rascacielos. De entre los proyectos realizados en esos años, este proceso de colaboración dió como resultado a al menos tres obras maestras: la torre Velasca, el rascacielos Pirelli y la torre de la Bolsa de Valores de Montreal. Esta última, en el momento de su finalización, además significó el récord del edificio de hormigón armado más alto del mundo.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.115
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.005
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0340.005

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 head0.004
GPT teacher head0.238
Teacher spread0.234 · 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
GenreEmpirical

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

Citations5
Published2020
Admission routes1
Has abstractyes

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