ArticleData in brief2019
RoCoLe: A
Article in Data in brief, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Robust coffee plant disease classification using deep learning and advanced feature engineering techniques.PeerJ. Computer science · 2025Article
- A review of deep learning architectures for plant disease detection.Turkish journal of biology = Turk biyoloji dergisi · 2025Review
- Review
- Deep transfer learning with gravitational search algorithm for enhanced plant disease classification.Heliyon · 2024Article
- LuffaFolio: A Multidimensional Image Dataset of Smooth Luffa.Data in brief · 2024Article
- Coffee and cashew nut dataset: A dataset for detection, classification, and yield estimation for machine learning applications.Data in brief · 2024Article
- Plant disease recognition datasets in the age of deep learning: challenges and opportunities.Frontiers in plant science · 2024Article
- Mint leaves: Dried, fresh, and spoiled dataset for condition analysis and machine learning applications.Data in brief · 2023Article
- The NWRD Dataset: An Open-Source Annotated Segmentation Dataset of Diseased Wheat Crop.Sensors (Basel, Switzerland) · 2023Article
- DIMPSAR: Dataset for Indian medicinal plant species analysis and recognition.Data in brief · 2023Article
- Dataset of groundnut plant leaf images for classification and detection.Data in brief · 2023Article
- CoLeaf-DB: Peruvian coffee leaf images dataset for coffee leaf nutritional deficiencies detection and classification.Data in brief · 2023Article
- Automatic Clustering and Classification of Coffee Leaf Diseases Based on an Extended Kernel Density Estimation Approach.Plants (Basel, Switzerland) · 2023Article
- PMVT: a lightweight vision transformer for plant disease identification on mobile devices.Frontiers in plant science · 2023Article
- Data-centric annotation analysis for plant disease detection: Strategy, consistency, and performance.Frontiers in plant science · 2022Article
- Resources for image-based high-throughput phenotyping in crops and data sharing challenges.Plant physiology · 2021Article
- Coffee Disease Visualization and Classification.Plants (Basel, Switzerland) · 2021Article
- Arabica coffee leaf images dataset for coffee leaf disease detection and classification.Data in brief · 2021Article
- Review of the State of the Art of Deep Learning for Plant Diseases: A Broad Analysis and Discussion.Plants (Basel, Switzerland) · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this article we introduce a
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.