MétaCan
Menu
Back to cohort
Record W3008939209

Caracterización y automatización mecánica de los telescopios Cherenkov de CASLEO

2017· article· es· W3008939209 on OpenAlexfundno aff
Nuno Leal, L. D. Yelós, A. Mancilla, Lilia Baranski Feres, Fabiola Lazarte, B. Garćıa

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2017
Typearticle
Languagees
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
FundersOffice of ScienceNational Astronomical Observatory of JapanNational Institutes of Natural SciencesConsejo Nacional de Investigaciones Científicas y TécnicasU.S. Department of EnergySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungComisión Nacional de Investigación Científica y TecnológicaUniversidad Nacional de La PlataNational Radio Astronomy ObservatoryNatural Sciences and Engineering Research Council of CanadaNational Science CouncilSmithsonian InstitutionUniversidad Nacional de San JuanKorea Astronomy and Space Science InstituteSecretaría de Ciencia y Técnica, Universidad de Buenos AiresNational Science Foundation
KeywordsHumanitiesPhysicsArt
DOInot available

Abstract

fetched live from OpenAlex

Se propone el reemplazo del sistema de motorización, ya obsoleto, de los telescopios Cherenkov del Complejo Astronómico El Leoncito (CASLEO). Se diseñó una cadena cinemática que trabaja con velocidad rápida para movimientos de posicionado y parking, y velocidad lenta para el movimiento de tracking. Como parámetro de diseño se utiliza la velocidad de viento promedio en El Leoncito. En este trabajo se presentan resultados preliminares que demuestran que los componentes seleccionados para la automatización del telescopio son capaces de cumplir con la velocidad rápida de giro.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.268
Teacher spread0.248 · 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 designBench or experimental
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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)Same topicParticle Detector Development and PerformanceFrench-language works237,207