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Record W2358802698

Development and Application Advances of Cloud Seeding Instruments

2014· article· en· W2358802698 on OpenAlexaboutno aff
Yan Shao

Bibliographic record

VenueJournal of Arid Meteorology · 2014
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Decision-Making Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSeedingWeather modificationEnvironmental scienceCloud seedingMeteorologyAeronauticsAerospace engineeringEngineeringGeography
DOInot available

Abstract

fetched live from OpenAlex

The history of weather modification activities lasted for nearly 70 years,with lots of development occurring in the seeding instruments and techniques,integrated air and ground operations system has formed. Countries such as USA,Canada,Australia,Israel,South Africa and Thailand mainly employ aircrafts and ground generators for weather modification. Countries such as Russia,China and Bulgaria carry out weather modification using aircrafts,ground generators as well as rockets or artilleries. Remarkable development and advancement achieved in seeding instruments technologies along with making use of high- powered aircraft,improvement of seeding technique and betterment of agents formulations. The paper separately introduced the development and application of aircrafts and onboard seeding equipment,rockets or artilleries,ground generators and common seeding agents at home and abroad,and their developing direction was discussed as well.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.280
Teacher spread0.270 · 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
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
Published2014
Admission routes1
Has abstractyes

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