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Record W2803904585 · doi:10.3390/atmos9050202

Nitric Oxide Production by Centimeter-Sized Meteoroids and the Role of Linear and Nonlinear Processes in the Shock Bound Flow Fields

2018· article· en· W2803904585 on OpenAlexafffund
Elizabeth A. Silber, M. L. Niculescu, Peter Butka, Reynold E. Silber

Bibliographic record

VenueAtmosphere · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaVedecká Grantová Agentúra MŠVVaŠ SR a SAVAgentúra na Podporu Výskumu a Vývoja
KeywordsMeteoroidShock (circulatory)Meteor (satellite)Context (archaeology)CentimeterShock wavePlasmaThermosphereEnvironmental sciencePhysicsDeposition (geology)Atmospheric sciencesAstrobiologyGeologyMechanicsMeteorologyAstronomyIonosphereNuclear physics

Abstract

fetched live from OpenAlex

Nitric oxide (NO) is a critical indicator of energy deposition in the lower thermosphere because of its formational pathways. Thus, it is important to constrain sources of NO, such as meteoroid generated hypersonic flows below 95 km altitude. This paper aims to examine the process of and place the upper estimate on NO production in high temperature flow fields of strongly ablating meteoroids. For centimeter-sized meteoroids, the production of NO is bound within the dynamically stable volume of bright meteor plasma trains in the region of 80–95 km. Our estimate of the upper limit of the cumulative mass of NO produced annually by centimeter-sized meteoroids is significantly lower than that reported in previous early studies. In the context of shock waves, we explored the reasons why centimeter-sized meteoroids are the most efficient producers of NO. Effects of nonlinear processes on meteoric NO production are discussed.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.189

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 head0.004
GPT teacher head0.197
Teacher spread0.194 · 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

Citations5
Published2018
Admission routes2
Has abstractyes

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