PATENT CLAIM ANALYSIS

Application Number: 15872395
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-05
Patent Classification: ["347", "110000"]

Abstract:
Modular print engines and print engine components that are usable in desktop card printers for personalizing plastic cards such as financial cards including credit and debit cards, identification cards, driver's licenses, and other personalized plastic cards. The modular nature of the print engines and print engine components permit alteration in the specific functionality of the desktop card printers depending upon, for example, the personalization requirements of the plastic cards and intended applications of the desktop card printers. In addition, the modular print engine components can be completely tested prior to installation into the modular print engines to ensure that the modular print engine components are working correctly prior to installation. Furthermore, the modular print engine components add flexibility to the desktop card printers as upgraded functionality and features can be introduced by developing new modular components.

Claim (Index 18):
The modular print engine of  claim 17 , wherein the second card opening is formed in the top of the housing, and further comprising a third card opening formed in the rear end of the housing through which a card can travel.

Metadata:
- Claim Count in Document: 32.0
- Percentile: 86.0
- Lexical Diversity: 2.14493
- Patent Class: 347.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15094462', '10716579', '15395309', '15178811', '12128897']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7435935371059483
- 35 USC 102 Novelty (BERT): 0.5811504935634101
- Combined Prediction Score: 0.7273492327516946
- Mean Citation Score: 261.91714800000005
- Max Citation Score: 505.4296
- Similarity Product: 434.903120112133

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test