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Record W3020056095 · doi:10.1061/9780784479971.058

LIRA LIBS for Stand-Off Planetary and Asteroid Resource Prospecting

2016· article· en· W3020056095 on OpenAlex
Vincent Latendresse, Roman V. Kruzelecky, Piotr Murzionak, Jonathan Lavoie, Elad Wallach, Alireza Nakhaei, Ian Sinclair, Wes Jamroz, E. A. Cloutis, P. Cottin, Michel Doucet

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEarth and Space 2016 · 2016
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsUniversity of WinnipegMPB Technologies & Communications (Canada)
FundersCanadian Space Agency
KeywordsProspectingAsteroidContext (archaeology)Remote sensingLiraBreadboardAstrobiologyPlanetary explorationGeologyEngineeringMars Exploration ProgramMining engineeringPhysics

Abstract

fetched live from OpenAlex

This paper discusses the laser-induced remote analyzer (LIRA) LIBS engineering breadboard, relevant verifications, and its potential application to future lunar and asteroid missions to assist the exploration and mapping of mineralogy and in situ resources. LIRA consists of a laser-induced breakdown spectrometer and imaging system that provides elemental data and context imaging for stand-off investigations of targets on planetary surfaces.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.186
Teacher spread0.179 · 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