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Record W3164454262 · doi:10.1007/s11214-021-00812-z

Perseverance’s Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) Investigation

2021· article· en· W3164454262 on OpenAlexfundno aff
R. Bhartia, L. W. Beegle, Lauren DeFlores, William Abbey, Joseph Razzell Hollis, Kyle Uckert, Brian Monacelli, K. S. Edgett, M. R. Kennedy, Margarite Sylvia, D. Aldrich, M. S. Anderson, Sanford A. Asher, Zachary Bailey, Kerry Boyd, Aaron S. Burton, Michael Caffrey, Michael J. Calaway, Robert J. Calvet, Bruce Cameron, M. A. Caplinger, Brandi L. Carrier, Nataly Chen, Amy Chen, S. M. Clegg, P. G. Conrad, Moogega Cooper, Kristine Davis, B. L. Ehlmann, Linda Facto, M. Fries, D. H. Garrison, Denine Gasway, Ferial Ghaemi, Trevor G. Graff, K. P. Hand, Cathleen M. Harris, J D Hein, Nicholas A. Heinz, Harrison Herzog, Eric B. Hochberg, Andrew Houck, William F. Hug, Elsa Jensen, Linda C. Kah, John M. Kennedy, Robert Krylo, Johnathan Lam, Mark Lindeman, Justin McGlown, John Michel, E. Miller, Zachary Mills, M. E. Minitti, Fai Mok, James D. Moore, Kenneth H. Nealson, Anthony Nelson, Raymond Newell, Brian Nixon, Daniel Nordman, D. L. Nuding, Sonny Orellana, Michael Pauken, Glen Peterson, Randy Pollock, Heather Quinn, Claire Quinto, M. A. Ravine, R. D. Reid, Joe Riendeau, Amy Ross, Joshua Sackos, J. A. Schaffner, Mark A. Schwochert, Molly O Shelton, Rufus Simon, C. L. Smith, P. Sobrón, Kimberly Steadman, A. Steele, Dave Thiessen, Tony Tsai, Michael Tuite, Eric Tung, Rami W. Wehbe, Rachel L. Weinberg, Ryan H. Weiner, R. C. Wiens, Kenneth H. Williford, Chris Wollonciej, Yen-Hung Wu, R. A. Yingst, Jason Zan

Bibliographic record

VenueSpace Science Reviews · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
FundersLos Alamos National LaboratoryHuman Exploration and Operations Mission DirectorateJohnson Space CenterJet Propulsion LaboratoryMinistère de la Santé et des Services sociauxNational Institute of Standards and TechnologyUniversities Space Research AssociationCalifornia Institute of TechnologyNational Aeronautics and Space Administration
KeywordsRaman spectroscopySpectrographOpticsContext (archaeology)Materials scienceChemical imagingMars Exploration ProgramRemote sensingLaserMonochromatorSpectroscopySpectrometerSpectral resolutionPhysicsHyperspectral imagingGeologySpectral lineAstrobiology

Abstract

fetched live from OpenAlex

Abstract The Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) is a robotic arm-mounted instrument on NASA’s Perseverance rover. SHERLOC has two primary boresights. The Spectroscopy boresight generates spatially resolved chemical maps using fluorescence and Raman spectroscopy coupled to microscopic images (10.1 μm/pixel). The second boresight is a Wide Angle Topographic Sensor for Operations and eNgineering (WATSON); a copy of the Mars Science Laboratory (MSL) Mars Hand Lens Imager (MAHLI) that obtains color images from microscopic scales (∼13 μm/pixel) to infinity. SHERLOC Spectroscopy focuses a 40 μs pulsed deep UV neon-copper laser (248.6 nm), to a ∼100 μm spot on a target at a working distance of ∼48 mm. Fluorescence emissions from organics, and Raman scattered photons from organics and minerals, are spectrally resolved with a single diffractive grating spectrograph with a spectral range of 250 to ∼370 nm. Because the fluorescence and Raman regions are naturally separated with deep UV excitation (<250 nm), the Raman region ∼ 800 – 4000 cm−1 (250 to 273 nm) and the fluorescence region (274 to ∼370 nm) are acquired simultaneously without time gating or additional mechanisms. SHERLOC science begins by using an Autofocus Context Imager (ACI) to obtain target focus and acquire 10.1 μm/pixel greyscale images. Chemical maps of organic and mineral signatures are acquired by the orchestration of an internal scanning mirror that moves the focused laser spot across discrete points on the target surface where spectra are captured on the spectrometer detector. ACI images and chemical maps (< 100 μm/mapping pixel) will enable the first Mars in situ view of the spatial distribution and interaction between organics, minerals, and chemicals important to the assessment of potential biogenicity (containing CHNOPS). Single robotic arm placement chemical maps can cover areas up to 7x7 mm in area and, with the < 10 min acquisition time per map, larger mosaics are possible with arm movements. This microscopic view of the organic geochemistry of a target at the Perseverance field site, when combined with the other instruments, such as Mastcam-Z, PIXL, and SuperCam, will enable unprecedented analysis of geological materials for both scientific research and determination of which samples to collect and cache for Mars sample return.

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)0.000
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 score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.016
GPT teacher head0.232
Teacher spread0.215 · 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

Citations240
Published2021
Admission routes1
Has abstractyes

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