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Record W2797400676 · doi:10.6000/1927-5129.2018.14.18

Spatio-Temporal and Physiographical Study of the Abandoned Sutlej River: A Case of Jhangi Wala, Bahawalpur, Pakistan

2018· article· en· W2797400676 on OpenAlexvenueno aff
Muhammad Iqbal, Muhammad Mushahid Anwar, Muhammad Nasar-u-Minallah, Khalil-Ur- Rehman, Noor Hussain Chandio, Konstantin Zakharov, Muhammad Mohsin, Muhammad Iqbal

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsRiparian zoneGeographySiltationGroundwater rechargeWater resource managementHydrology (agriculture)GroundwaterEnvironmental scienceHabitatAquiferEcologyGeology

Abstract

fetched live from OpenAlex

Rivers are the sign of prosperity, the hub of the economy and act as lifeline for the areas from where they flow. Rivers help in irrigation, ground water recharge, upgrading water quality, maintaining soil fertility, fostering forests. They also support in stabilizing industries, establishing cities and towns. Revirs are the sources of energy generation, enhancing tourism, managing wetlands, boosting fishing, avoiding desertification, droughts, famine and empowering people by providing employment opportunities. Rivers might stop flowing in any area through climatic changes, river piracy, and upper riparian monopoly. Sutlej River is now not flowing in Pakistan due to damming at its upper riparian (India) after the Indus Basin Water Treaty. In this paper, efforts are made to know about evolutionary processes through which Sutlej River passed from the old days and its present cruel and politicized abundance by the upper riparian. The main objective of the paper is to furnish a preliminary data base about Pakistan side (lower riparian) of the Sutlej River. Fact and figures used are mainly from the secondary sources and few primary sources and direct observations. By exploring and knowing about its spatial pattern, temporal evolutions, geographical, geological and physiographical changes and all the processes concerned to the river, it will be possible for us to educate our future generation about the conversion of past mighty and splendid Sutlej River into an abandoned River.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.315
Teacher spread0.291 · 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 designQualitative
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
Published2018
Admission routes1
Has abstractyes

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