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Spatial and Temporal Distribution of Frost in Jordan

2011· article· en· W2595406086 on OpenAlexvenueno aff
Ibrahim M. Oroud

Bibliographic record

VenueArab world geographer · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Drought Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFrost (temperature)Physical geographyGeographyHazardDesertificationMeteorologyEcology

Abstract

fetched live from OpenAlex

Surface frost is a permanent natural hazard that affects almost all areas in Jordan. Daily grass minimum temperatures at seven stations representing the three geographic zones (the Jordan Valley, mountains, and desert) in the country were used to carry out the analysis. A set of years ranging from 68 (for Amman Airport) to 24 years was used in this investigation. Data were tested for normality using a variety of robust statistical procedures. The main objective of the present study is to describe the stochastic nature of frost at these stations. Early and late frost and number of frost-free days were extracted in this investigation. Frost in Jordan occurs as early as the beginning of October, and late frost can last until May or even as late as June, as is the case in the southern mountains. The probability of early and late dates of frost is presented for the various stations. Compensation provided by the government should take into account the probability of frost hazard before / after the date of occur...

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)0.000
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 score0.027
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0030.000

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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
Published2011
Admission routes1
Has abstractyes

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