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Record W2896422582 · doi:10.1117/12.2515121

On development of cross-platform software to continue long-term observations with the Brewer Ozone Spectrophotometer

2018· article· en· W2896422582 on OpenAlexaboutno aff
Vladimir Savinykh, O. V. Postylyakov

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceSoftwareCodebaseCross-platformOperating systemRendering (computer graphics)Software engineering

Abstract

fetched live from OpenAlex

Observed since 1998 recovery of the ozone layer likely caused by prohibiting some ozone-depleting substances under the Montreal Protocol may be unstable. Therefore the homogeneity of the ozone observations in comparison with data of previous decades continues to be important. The network of fully automated Brewer spectrophotometers operated since the earlier 1980s is one of the oldest global systems providing data for the ozone assessments. The existing software for control Brewer spectrophotometers was created more than 35 years ago and is in need of redeveloping to continue the long-term observations in the face of changing computer platforms. New cross-platform operating software for the Brewer is under development by a group of researchers from OIAP of RAS. The software is capable of running on computers with modern multitasking operating systems (Windows, Linux, macOS), and at the same time it has one codebase. In the new Brewer operating software, the Model/View architecture is implemented to separate the code of measurement data (models) from the code of rendering this data to the user or spectrophotometer (views). The model is responsible for data management and provides an interface for reading and writing this data, and the view retrieves the necessary data from the model, reacting to its changes, and sends the data to the user (or spectrophotometer), placing them properly in the GUI of application or into the serial port interface to which a spectrophotometer is connected. Models are developed in the C++ programming language using the cross-platform Qt framework, while the relational database SQLite is used as a persistent storage. The developed database of the new software for storing measurement data and instrumental constants consists of more than 30 tables and stores about 800 pieces of information. This software allows keeping the quality and uniformity of ozone and UV-radiation measurements on the Brewer spectrophotometers of the global ozone network.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0140.015

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 head0.029
GPT teacher head0.255
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations4
Published2018
Admission routes1
Has abstractyes

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