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repoGitLabTrust 82 · PrimaryPublished 1mo agoLive · 2d ago

April.Wu/stage-specific-causal-machine-learning-for-potato-yield-response-to-water-deficit-and-excess

A reproducible causal machine-learning pipeline for estimating stage-specific potato-yield responses to water deficit and excess, diagnosing empirical overlap, and translating dose–response estimates into irrigation decision-support indicators.

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

  • PossiblePossibly related (embedding) · 48%Agriculture is ready for AI, but its data isn’t →
  • PossiblePossibly related (embedding) · 46%University of Tokyo and Kubota Develop Drone Potato Yield Prediction Method - Dronelife →
  • PossiblePossibly related (embedding) · 51%Operational evidence standards for machine learning in wastewater treatment - Nature →

Covers

newsAgriculture is ready for AI, but its data isn’tnewsUniversity of Tokyo and Kubota Develop Drone Potato Yield Prediction Method - Dronelife

Covers (incoming)

newsOperational evidence standards for machine learning in wastewater treatment - Nature

Related across the graph

newsAgriculture is ready for AI, but its data isn’tnewsOperational evidence standards for machine learning in wastewater treatment - NaturenewsUniversity of Tokyo and Kubota Develop Drone Potato Yield Prediction Method - Dronelife
Knowledge path·NAgriculture is ready for AI, but its data isn’t→NOperational evidence standards for machine learning in wastewater treatment - Nature→NUniversity of Tokyo and Kubota Develop Drone Potato Yield Prediction Method - Dronelife→RApril.Wu/stage-specific-causal-machine-learning-for-potato-yield-response-to-water-deficit-and-excess

Topics

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