MétaCan
Menu
Back to cohort
Record W3138567652 · doi:10.1109/lra.2021.3067281

Rover Relocalization for Mars Sample Return by Virtual Template Synthesis and Matching

2021· article· en· W3138567652 on OpenAlexaff
Tu-Hoa Pham, William Seto, Shreyansh Daftry, Barry Ridge, Johanna Hansen, Tristan Thrush, Mark Van der Merwe, Gerard Maggiolino, Alexander Brinkman, John Mayo, Yang Cheng, Curtis Padgett, Eric Kulczycki, Renaud Detry

Bibliographic record

VenueLirias (KU Leuven) · 2021
Typearticle
Languageen
FieldEngineering
TopicRobotics and Sensor-Based Localization
Canadian institutionsMcGill University
FundersCalifornia Institute of TechnologyJet Propulsion LaboratoryNational Aeronautics and Space Administration
KeywordsTerrainMars Exploration ProgramRobustness (evolution)Computer scienceSample (material)Context (archaeology)Artificial intelligenceMatching (statistics)Computer visionSet (abstract data type)Computer graphics (images)GeographyCartographyMathematicsAstrobiologyStatistics

Abstract

fetched live from OpenAlex

sponsorship: This letter was recommended for publication by Associate Editor S. Behnke and Editor S. Bernard Williams upon evaluation of the reviewers' comments. This work was supported in part by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. (Jet Propulsion Laboratory, California Institute of Technology, National Aeronautics and Space Administration)

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.004

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 head0.009
GPT teacher head0.205
Teacher spread0.195 · 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
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

Citations10
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueLirias (KU Leuven)Same topicRobotics and Sensor-Based LocalizationFrench-language works237,207