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Record W1530451419 · doi:10.54782/001c.132939

Current Status and Future Direction of the Oklahoma Weather Modification Program

2000· article· en· W1530451419 on OpenAlexaboutno aff
Nathan R. Kuhnert, Brian R Vance, Michael E. Mathis

Bibliographic record

VenueThe Journal of Weather Modification · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsnot available
Fundersnot available
KeywordsWeather modificationLegislatureState (computer science)Environmental resource managementBusinessEnvironmental scienceEngineeringEnvironmental planningMeteorologyPolitical scienceComputer scienceGeography

Abstract

fetched live from OpenAlex

The primary focus of the Oklahoma Weather Modification Program is to suppress hail and augment rainfall. Initiated in the fall of 1996, the demonstration program is patterned after similar successful efforts underway in Kansas, North Dakota, Texas and Alberta, Canada. In 1997 and 1998, the statewide program incorporated an independent evaluation to measure results, although no randomized cloud seeding operations were conducted. Results of the evaluation are promising. Prompted, in part, by the need for additional resources to implement the program at the desired capacity, the State Legislature passed legistation in 1999 to create a cooperative, long-term funding mechanism between state and the Oklahoma’s insurance industry. Potential interstate cooperation with weather modification efforts in Texas and Kansas bode well for the continuation and future growth of the program.

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)0.008
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.115
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.004
Open science0.0030.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0230.003

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 head0.015
GPT teacher head0.250
Teacher spread0.235 · 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 designNot applicable
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

Citations2
Published2000
Admission routes1
Has abstractyes

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