PATENT CLAIM ANALYSIS

Application Number: 15907748
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-08
Patent Classification: ["358", "497000"]

Abstract:
A flatbed scanner document scanner includes a large format document scanner body accommodating a rectangular rigid frame with an upwardly facing plane face and a rectangular transparent plate for supporting a large format document. The rectangular transparent plate overlies the upwardly facing plane face all around the metal frame. The scanner also includes a movable carriage configured to move along and below the rectangular transparent plate and carrying a line camera extending across the rectangular transparent plate. The rectangular transparent plate and the metal frame are bonded together by a hard glue seam that runs on the upwardly facing plane face of the metal frame. A predetermined deflected shape can be formed when the bonded plate and frame are turned upside-down. The rectangular metal frame can deform under its own load to a cambered shape, a flat shape or a less deflected shape when turned upright in a normal position.

Claim (Index 4):
A flatbed scanner according to  claim 1 , wherein at least a pair of opposite frame elements are configured with torsion about a longitudinal axis of a respective frame element causing a twist of the frame elements which is balanced by the rigid bond between the transparent plate and the frame.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 88.0
- Lexical Diversity: 2.01282
- Patent Class: 358.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15908216', '12502053', '12822748', '10063739', '11124976']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5136490941213592
- 35 USC 102 Novelty (BERT): 0.5182025425482284
- Combined Prediction Score: 0.5141044389640461
- Mean Citation Score: 188.85267800000003
- Max Citation Score: 302.5769
- Similarity Product: 223.57205325148703

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

Dataset: test