PATENT CLAIM ANALYSIS

Application Number: 15758775
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-10
Patent Classification: ["426", "466000"]

Abstract:
A method and an apparatus for roasting a food product including: loading a batch of a predetermined food product type in a roasting device; setting operating parameters of the roasting device according to initial reference values for the predetermined food product type; performing feedback control during the heating of the product by obtaining, instant by instant, a value for a sound quantity which is relative to a sound emitted by the product, the sound being detected in a frequency range including both human ear audible and ultrasound frequencies; comparing the sound quantity's value obtained at each instant to a value taken by the sound quantity at such instant in a roasting curve of sound quantity versus time associated with the predetermined food product type; and adjusting, instant by instant, the operating parameters of the roasting device depending on the result of the comparison.

Claim (Index 7):
Method according to  claim 6 , also comprising a step of verifying that the comparison of the sound quantity value is carried out based on a roasting curve of said sound quantity versus time, which is actually associated with the food product type thus identified.

Metadata:
- Claim Count in Document: 12.0
- Percentile: 90.0
- Lexical Diversity: 2.12329
- Patent Class: 426.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['14932325', '15180780', '13529838', '11535479', '10043873']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7271574299480489
- 35 USC 102 Novelty (BERT): 0.4984357132661521
- Combined Prediction Score: 0.7042852582798592
- Mean Citation Score: 199.719626
- Max Citation Score: 209.11252
- Similarity Product: 133.03941912213324

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