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Record W1607250175

THIRTY METER TELESCOPE (TMT) SITE MERIT FUNCTION

2011· article· es· W1607250175 on OpenAlexfundvenueno aff
Matthias Schöck, J. Stuart Nelson, S. Els, P. Gillett, Ángel Otarola, Reed Riddle, Warren Skidmore, Tony Travouillon, Robert Blum, G. A. Chanan, De Young, S. G. Djorgovski, Derrick Salmon, Eric Steinbring, A. Walker

Bibliographic record

VenueNPARC · 2011
Typearticle
Languagees
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
FundersOntario Ministry of Research and InnovationBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaAssociation of Canadian Universities for Research in AstronomyCalifornia Institute of TechnologyGordon and Betty Moore FoundationNational Science Foundation
KeywordsPhysicsTelescopeMetreFunction (biology)Figure of meritRemote sensingAstronomyOpticsGeography
DOInot available

Abstract

fetched live from OpenAlex

TMT collected a large multi-dimensional data set of site characteristics at its five candidate sites. In order to make an informed site decision, this data set was reduced to a one dimensional metric, the site merit function. This paper describes examples of some of the coefficients of this merit function, with an emphasis on the interpretation of the results of such an approach and its limitations. © 2011: Instituto de Astronomía, UNAM - Astronomical Site Testing Data in Chile Ed. M. Curé, A. Otárola, J. Marín, & M. Sarazin.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.015
GPT teacher head0.196
Teacher spread0.181 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations2
Published2011
Admission routes2
Has abstractyes

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