Results 131 to 140 of about 318,360 (330)

Determinants of local food producer participation in state‐sponsored marketing programs: Evidence from Missouri

Agribusiness, EarlyView.
Abstract This study examines producer participation choices considering a variety of potential benefits linked to state‐sponsored marketing programs, using a real choice dataset of farmers in Missouri. Multinomial logit models are employed to predict determinants of farmer enrollment in three tiers of the Missouri Grown local food marketing program ...
Lan Tran, Ye Su, Laura McCann
wiley   +1 more source

Monitoring named entity recognition: the League Table [PDF]

, 2013
Dietrich Rebholz‐Schuhmann, Şenay Kafkas, Jee-Hyub Kim, Antonio Jimeno Yepes, Ian Lewin   +4 more
openalex   +1 more source

Dataset for Named Entity Recognition and Entity Linking from Greek Wikipedia Events

, 2022
Katerina Papantoniou, Vasilis Efthymiou, Dimitris Plexousakis   +2 more
openalex   +1 more source

The Role of Coordination Mechanisms and Transaction Costs Promoting Sustainability Performance in Agri‐Food Supply Chains: Evidence From Ecuador

Agribusiness, EarlyView.
ABSTRACT Social tensions and resource depletion pose significant challenges to the agri‐food sector, highlighting the need for coordinated strategies to ensure sustainability in supply chains. Despite its critical importance, the relationship between coordination mechanisms and sustainability performance remains underexplored.
Carlos Moreno‐Miranda, Liesbeth Dries
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

FloraNER: A new dataset for species and morphological terms named entity recognition in French botanical text

Data in Brief
FloraNER is a distantly supervised named entity recognition dataset (NER). The dataset is built from botanical French literature extracted from the OCR-preprocessed flora of New Caledonia, provided by the National Museum of Natural History in France ...
Ayoub Nainia, Régine Vignes-Lebbe, Eric Chenin, Maya Sahraoui, Hajar Mousannif, Jihad Zahir   +5 more
doaj   +1 more source

Active learning with feature matching for clinical named entity recognition

, 2023
Linh Le, Gianluca Demartini, Guido Zuccon, Genghong Zhao, Xia Zhang   +4 more
openalex   +1 more source

Beheshti-NER: Persian Named Entity Recognition Using BERT [PDF]

, 2020
Ehsan Taher, Seyed Abbas Hoseini, Mehrnoush Shamsfard   +2 more
openalex   +1 more source

Robust Self-Augmentation for Named Entity Recognition with Meta Reweighting [PDF]

, 2022
Linzhi Wu, Pengjun Xie, Jie Zhou, Meishan Zhang, Siwei Ma, Guangwei Xu, Min Zhang   +6 more
openalex   +1 more source

Named Entity Recognition Models for Machine Learning Interatomic Potentials: A User‐Centric Approach to Knowledge Extraction from Scientific Literature

Advanced Intelligent Discovery, EarlyView.
Named entity recognition pipeline for knowledge extraction from scientific literature. Machine learning interatomic potential (MLIP) is an emerging technique that has helped achieve molecular dynamics simulations with unprecedented balance between efficiency and accuracy. Recently, the body of MLIP literature has been growing rapidly, which propels the
Bowen Zheng, Grace X. Gu
wiley   +1 more source