MétaCan
Menu
Back to cohort
Record W2477578314

Large Scale Reclamation of waterlogged saline soils in chambal command area, Rajasthan

2016· article· en· W2477578314 on OpenAlexaboutno aff
C. M. Tejawat

Bibliographic record

VenueWater and Energy International · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRice Cultivation and Yield Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsWaterlogging (archaeology)DrainageLand reclamationSoil salinitySalinityEnvironmental scienceDNS root zoneAgricultureSalineHydrology (agriculture)CropSoil waterAgronomyEngineeringGeologySoil scienceBiologyOceanographyEcologyGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

The Rajasthan Agricultural Drainage Research (RAJAD) Project aided by Canadian International Development Agency was introduced in 1992 to combat the problems of salinity and waterlogging in the Chambal Command Area (CCA), using the horizontal subsurface drainage (SSD) technology. A significant reduction in the crop yield in saline and waterlogged land compared to non-saline and non-waterlogged land in the Chambal Command Area was found. Sub Surface drainage was mainly provided to control water table depth at a pre-determined level; to allow enhanced root development of crops; to leach excess salts and prevent salt accumulation within the root zone at levels higher than the tolerance level of crops; and to provide enhanced soil trafficability during growing season.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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 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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueWater and Energy InternationalSame topicRice Cultivation and Yield ImprovementFrench-language works237,207