The phrase "agreement score" is correct and usable in written English.
It can be used in contexts where you are measuring or evaluating the level of agreement between parties or items, such as in surveys or data analysis.
Example: "The agreement score between the two groups was surprisingly high, indicating a strong consensus on the issue."
Alternatives: "consensus score" or "accord rating".
The achievement of these goals determines the management agreement score.
Considering the inter-annotator agreement score of 91%, the model demonstrates near-human performance.
However, CrowdFlower has been shown to produce an agreement score that compares well to these classic measures [19].
A percentage agreement score is then given, with a score between 70 97 % deemed acceptable (Berke et al. 2012).
CrowdFlower provides an agreement score for each annotated unit, which is based on the majority vote of the trusted workers [19].
These videos were then categorized as valid emotional samples or not, based on an agreement score of at least 90%% of the expected values shown in Table 1.
The resulting value, called inter-annotator agreement (IAA) or inter-coder agreement score is useful to assess how well the task is defined, how consistent the annotations are and it helps to quantity the difficulty of the annotation process.
This is a dichotomy variable in which public hospitals, denoted by an H, took a value 0, and PPP Hospitals denoted by a C, took a value 1. Management agreement score.
Due to many difficulties inherent to chemical entity detection and normalisation [1], even manual annotation yields the inter-annotator agreement score of 91%, which can be regarded as the theoretical limit for any automatic system trained on this corpus.
In addition, according to results given in Table 3, the proposed system using four gestalt factors has the highest agreement score with P = 0.875 and can be used to represent the human choices.
Because although the agreement score is 15 20% lower than Zhou and Xue (2012) and Zhou et al. (2014), they only deal with discourse relation and label coarse-grained sense relation.
