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Record W2790791886 · doi:10.22323/1.301.0076

Subauroral mesopause temperature response to solar activity in 1999-2013

2017· article· en· W2790791886 on OpenAlexaboutno aff
Анастасия Аммосова, Galina Gavrilyeva, Петр Аммосов, Igor Koltovskoi

Bibliographic record

VenueProceedings of 35th International Cosmic Ray Conference — PoS(ICRC2017) · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersRussian Foundation for Basic Research
KeywordsAtmospheric sciencesMesopauseEnvironmental scienceSolar cycleSpectrographTemperature measurementResidualFlux (metallurgy)MeteorologyMaterials sciencePhysicsThermodynamicsMathematicsMesosphereSpectral lineSolar windAstronomy

Abstract

fetched live from OpenAlex

OH(6-2) rotational temperature trends and solar cycle effects are studied. Observations were carried out at the Maimaga station (63.04° N, 129.51° E) for the period August 1999 to March 2013. Measurements were conducted with an infrared spectrograph. The temperature was determined by P- branch ratio of the molecular of hydroxyl. The monthly average residuals of temperature after the subtraction of seasonal climatic component were used for a search for the solar component of temperature response. The dependence of temperatures on solar activity has been investigated using the Ottawa 10.7 cm flux as a proxy. A linear regression fitting on residual temperatures yields a solar cycle coefficient of 4.24 K /100 solar flux units (SFU). The cross-correlation analyses showed that changes of the residual temperature follow changes of solar activity with a 25 months delay. The temperature response at the delay of 25 months reaches 7 K/100 SFU. The value of the temperature trend after the subtraction of seasonal and solar components inconsiderable. The effect of geomagnetic activity on the subauroral mesopause temperature was evaluated to find the possible reasons for the time lag.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.023
GPT teacher head0.263
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.

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
Published2017
Admission routes1
Has abstractyes

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