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Record W4411324649 · doi:10.53762/9gh1xr92

10.53762/9gh1xr92

2000· article· en· W4411324649 on OpenAlexvenueno aff
Saifullah, Lutfullah Saqib, Saeed ur Rahman

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic, Cultural, and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Being benefited by the favors of Allah Ta'ala, man is eager to find more facilities for himself every time and is busy day and night to make every area of ​​life easier. But it is also surprising that on the one side, man wants facilities for himself, while on the other side, sometimes these facilities are the cause of death. As in earlier times people used to travel on Donkey Carts, Camels etc. Then times changed and engines started being used, people started traveling in cars. Development progressed until the time of the airplane came. People traveled the journey of month in hours. But along with this accidents also started to increase. Accidents in the past caused very few deaths, while today's accidents cause many deaths or at least maiming and injuring the human body or causing financial loss. After which the parties file various claims against each other. Therefore, keeping in mind the Islamic principle, it is necessary to resort to Sharia law to solve these problems. Because nowadays traffic usage is very high due to the abundance of people and it is increasing day by day. Due to which traffic problems are also faced more. Therefore, all countries and states issue orders for the traffic problems like all others problems of the country. For this reason, the Wali Swat also issued some orders for the residents of his successful state. Six of these orders are mentioned in the Riwaj Nama Swat, which are being reviewed in the light of Sharia in this article.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.494
Threshold uncertainty score0.507

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9800.931

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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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