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Record W3183506055 · doi:10.1089/ast.2021.0006

UV Time-Resolved Laser-Induced Fluorescence Spectroscopy of Amino Acids Found in Meteorites: Implications for Space Science and Exploration

2021· article· en· W3183506055 on OpenAlexaff
Elizabeth A. Lymer, Menelaos Konstantinidis, E.A. Lalla, M. G. Daly, K. T. Tait

Bibliographic record

VenueAstrobiology · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsRoyal Ontario MuseumPublic Health OntarioUniversity of TorontoYork University
Fundersnot available
KeywordsMurchison meteoriteMeteoriteAsteroidSpectroscopyAstrobiologyFluorescenceAllende meteoriteFluorescence spectroscopyLaser-induced fluorescenceMars Exploration ProgramTime-resolved spectroscopyChemistryCarbonaceous chondriteMeteoroidLaser-induced breakdown spectroscopyMaterials scienceAnalytical Chemistry (journal)OpticsPhysicsChondriteEnvironmental chemistryAstronomy

Abstract

fetched live from OpenAlex

Laser-induced fluorescence spectroscopy is a useful laboratory and in situ technique for planetary exploration, with applications in biosignature detection and the search for life on Mars. However, little work has been completed on the utility of fluorescence spectroscopy techniques on asteroid relevant material. In preparation for asteroid sample return missions such as NASA's OSIRIS-REx and JAXA's Hayabusa2, we conducted UV time resolved laser-induced fluorescence spectroscopy (TR-LIF) analysis of 10 amino acids, all of which have been found in the carbonaceous meteorites Murchison and Allende. We present the calculation of decay rates of each amino acid (1.55–3.56 ns) and compare with those of relevant homogeneous minerals (15–70 ns). Moreover, we demonstrate a linear relationship between calculated lifetimes and elemental abundance of nitrogen and carbon ( p < 0.025). The quantitative and qualitative fluorescence analyses presented in this work will lead to more reliable identification of organic material within meteorites and asteroids in a time-efficient, minimally destructive way.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.401

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 head0.021
GPT teacher head0.270
Teacher spread0.249 · 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 teacher head, 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

Citations8
Published2021
Admission routes1
Has abstractyes

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