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Record W2558843456 · doi:10.5194/angeo-34-1119-2016

Decay times of transitionally dense specularly reflecting meteor trails and potential chemical impact on trail lifetimes

2016· article· en· W2558843456 on OpenAlexafffund
W. K. Hocking, Reynold E. Silber, J. M. C. Plane, Wuhu Feng, Marcial Garbanzo‐Salas

Bibliographic record

VenueAnnales Geophysicae · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsWestern University
FundersEuropean Research CouncilNatural Sciences and Engineering Research Council of CanadaUniversidad de Costa RicaNatural Environment Research CouncilSight Research UK
KeywordsMeteor (satellite)MeteoroidMesosphereAtmospheric sciencesEnvironmental scienceGeologyMeteorologyPhysicsAstrophysicsAstrobiologyStratosphere

Abstract

fetched live from OpenAlex

Abstract. Studies of transitionally dense meteor trails using radars which employ specularly reflecting interferometric techniques are used to show that measurable high-temperature chemistry exists at timescales of a few tenths of a second after the formation of these trails. This is a process which is distinct from the ambient-temperature chemistry that is already known to exist at timescales of tens of seconds and longer in long-lived trails. As a consequence, these transitionally dense trails have smaller lifetimes than might be expected if diffusion were the only mechanism for reducing the mean trail electron density. The process has been studied with four SKiYMET radars at latitudes varying from 10 to 75° N, over a period of more than 10 years, 24 h per day. In this paper we present the best parameters to use to represent this behaviour and demonstrate the characteristics of the temporal and latitudinal variability in these parameters. The seasonal, day–night and latitudinal variations correlate reasonably closely with the corresponding variations of ozone in the upper mesosphere. Possible reasons for these effects are discussed, but further investigations of any causative relation are still the subject of ongoing studies.

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 score0.201
Threshold uncertainty score0.884

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)0.0010.000

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 head0.248
Teacher spread0.241 · 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

Citations13
Published2016
Admission routes2
Has abstractyes

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