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Record W2915431363 · doi:10.3103/s1068373915090095

Ozone content over the Russian Federation in the second quarter of 2015

2015· article· en· W2915431363 on OpenAlexaboutno aff
A. M. Zvyagintsev, N. S. Ivanova, G. M. Kruchenitskii, И. Н. Кузнецова, V. A. Lapchenko

Bibliographic record

VenueRussian Meteorology and Hydrology · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
Fundersnot available
KeywordsObservatoryQuarter (Canadian coin)Russian federationMeteorologyEnvironmental scienceSatelliteOzoneRemote sensingGeographyPhysicsRegional scienceAstronomy

Abstract

fetched live from OpenAlex

The review is compiled on the basis of the results of the operation of the total ozone (TO) monitoring in the CIS and Baltic countries functioning in the operational regime at the Central Aerological Observatory (CAO). The monitoring system uses the data from the national network obtained with M-124 filter ozonometers under the methodological supervision of the Main Geophysical Observatory. The quality of the functioning of the entire system is under operational control based on the observations obtained from the OMI satellite equipment (NASA, the United States). The basic TO observation data are generalized for each month of the second quarter of 2015 and for the quarter as a whole. The results of the regular observations of surface ozone content carried out in the Moscow region and Crimea are also provided.

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 categoriesInsufficient 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 score0.033
Threshold uncertainty score0.999

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)0.0020.000

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 head0.024
GPT teacher head0.236
Teacher spread0.213 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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