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Record W3159319396

Primordial Sulfur and the Origin of Life

2019· article· en· W3159319396 on OpenAlexaff
Amanda Coyle

Bibliographic record

VenueStudent Research Proceedings · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsMacEwan University
Fundersnot available
KeywordsMeteoriteHydrosphereSulfurAstrobiologyAbiogenesisChemistryEarth (classical element)Early EarthEarth scienceGeologyBiospherePhysicsOrganic chemistryEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

The study of meteorites can give insight regarding the chemical composition that was present when the solar system was being created. The elements in meteorites have not undergone extensive changes since they were formed billions of years ago, so they are thought to resemble those on Earth before the formation of the hydrosphere. This can lead to information regarding the formation of the solar system, Earth, and consequently, life. Sulfur is of interest because it has essential roles in biochemistry and a prevailing theory regarding the origin of life is that it began in an iron-sulfur world. By determining the sulfur composition of meteorites and the isotopic ratios – ratio of atoms of the same element with different atomic masses – we hope to determine the processes behind for formation of the form of sulfur responsible for the creation of life. This first stage of the project was to perfect wet chemistry and analytical techniques to extract and quantify sulfur species from meteorites. The development of the techniques required reading research literature, testing, and altering the techniques while working with a meteorite simulant. Multiple extractions with different solvents were used to differentially separate the sulfur species based on their chemical and physical properties. These initial techniques have been modified and applied to other meteorites. They will continue to be improved upon.   Faculty Mentor: Robert Hilts Department: Chemistry

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.044
GPT teacher head0.354
Teacher spread0.309 · 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 designObservational
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

Citations0
Published2019
Admission routes1
Has abstractyes

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