PATENT CLAIM ANALYSIS

Application Number: 16410480
Application Type: Utility
Filing Date: 2019-05
Publication Date: 2019-08
Patent Classification: ["702", "179000"]

Abstract:
A method for identifying the presence of at least one adulterant substance in a sample. The method comprises receiving sets of sample spectral data, reference spectral data, validation spectral data each set for a respective validation example, and adulterant substance spectral data for said at least one adulterant substance. From these residue data which is representative of a residue which would remain after performing a least squares fitting process between the sample spectral data and the reference spectral data is determined and modified sample residue data which is representative of a residue which would remain after performing a least squares fitting process between the sample spectral data, the reference spectral data and the adulterant substance spectral data is determined. The corresponding two residue data sets are also determined for each validation example. The method then includes performing least one comparison amongst the sample residue data, the modified sample residue data, the validation residue data, and the modified validation residue data; and determining a likelihood value for the presence of said at least one adulterant substance in said sample in dependence on said at least one comparison; and outputting said likelihood value.

Claim (Index 46):
A spectrometer arranged for identifying the presence of at least one adulterant substance in a physical sample, the spectrometer comprising:\n an analysis module to receive (i) a set of sample spectral data acquired for a sample, (ii) a plurality of sets of calibration spectral data for use in generating a set of reference spectral data, each set of calibration spectral data being for a respective calibration example, (iii) a plurality of sets of validation spectral data, each set for a respective validation example, (iv) a set of adulterant substance spectral data for said at least one adulterant substance, the analysis module further programmed to develop a principal components analysis model of the calibration sets of data to produce a set of principal factors which represent the set of reference spectral data; a spectral data processor executing on the analysis module to: a) project the principal factors out of the sample spectral data to leave sample residue data; project the principal factors out of each set of validation spectral data to leave validation residue data for each validation example; project the principal factors out of the adulterant substance spectral data for said at least one adulterant substance to leave adulterant residue data; least squares fit the sample residue data with the adulterant residue data to generate modified sample residue data, which represents an effect of taking the adulterant spectral data into account in the principal components analysis model; least squares fit the validation residue data with the adulterant residue data to generate the modified validation residue data, which represents an effect of taking the adulterant spectral data into account in the principal components analysis model, b) perform at least one comparison amongst the sample residue data, the modified sample residue data, the validation residue data, and the modified validation residue data; c) determine a likelihood value for the presence of said at least one adulterant substance in said sample in dependence on said at least one comparison; wherein the analysis module is programmed to generate using the likelihood value, a label for the adulterant substance indicating a likelihood that the adulterant substance is present in the physical sample.

Metadata:
- Claim Count in Document: 5.0
- Percentile: 100.0
- Lexical Diversity: 3.30645
- Patent Class: 702.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['14913782', '10937248', '14420101', '15486333', '15986918']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1549817437408555
- 35 USC 102 Novelty (BERT): 0.633618081410145
- Combined Prediction Score: 0.2028453775077844
- Mean Citation Score: 259.145544
- Max Citation Score: 587.3242
- Similarity Product: 551.0617647311807

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