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Record W4386361096 · doi:10.3847/25c2cfeb.d6cc0b85

The Next Generation Arecibo Telescope (NGAT)

2023· article· et· W4386361096 on OpenAlexaff
D. Anish Roshi, Nestor Apnote, E. D. Araya, Héctor G. Arce, Lisa‐Jane Baker, Willem A. Baan, Tracy M. Becker, James K. Breakall, Robert G. Brown, C. G. M. Brum, M. Busch, Donald Campbell, Tyler Cohen, Francisco Cordova, J. S. Deneva, Maxime Devogèle, Timothy Dolch, F. Fernandez-Rodriquez, Tapashree Ghosh, P. F. Goldsmith, Leonid Gurvits, Martha P. Haynes, Carl Heiles, Dylan Hickson, Bret Isham, Robert Kerr, John D. Kelly, John J. Kiriazes, Sid Kumar, J. Lautenbach, M. Lebrón, N. Lewandowska, Loris Magnani, P. K. Manoharan, S. Marshall, Anna McGilvray, Abel Méndez, Robert Minchin, V. Negrón, M. C. Nolan, L. Olmi, F. Paganelli, N. Palliyaguru, Z. Paragi, Stephen C. Parshley, J. E. G. Peek, Benetge B. P. Perera, Philip Perillat, N. Pinilla-Alonso, Luis Quintero, H. A. Radovan, S. Raizada, Timothy Robishaw, Matthew Route, Christopher J. Salter, Alfredo Santoni, Sukanta Sau, Sravani Vaddi, Fábio Vargas, Flaviane Venditti, A. Venkataraman, Anne Virkki, Amit Vishwas, S. Weinreb, Dan Werthimer, Alex Wolszczan, L. F. Zambrano-Maria

Bibliographic record

Venuenot available
Typearticle
Languageet
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAstronomyTelescopeRemote sensingPhysicsGeology

Abstract

fetched live from OpenAlex

Whitepaper #344 in the Decadal Survey for Solar and Space Physics (Heliophysics) 2024-2033. Main topics: basic research; infrastructure/workforce/other programmatic. Additional topics: other basic research; ground-based missions/projects; research tools and infrastructure.

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)0.005
metaresearch head score (Gemma)0.003
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 score0.066
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0400.020

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 head0.091
GPT teacher head0.320
Teacher spread0.230 · 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
Published2023
Admission routes1
Has abstractyes

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