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Option B is correct because if a table cell is empty, the Document AI model will not return a 'value' key for that cell, but it will still return the 'score' key, indicating its confidence that the cell is empty. Option C is correct because for successfully extracted entities, the JSON output for fields like 'net_profit typically includes an array of objects, where each object contains both a 'score' and a 'value' key. Option D is correct because the 'ocrScore' field within '_documentMetadata' is always present in the root of the JSON output, specifying the confidence score for the optical character recognition process for the document. Option A is incorrect; when an entity like 'audit_statuS is not found, the model omits the 'value' key, rather than setting it to 'null'. Option E is incorrect because if the Document AI model does not find an answer for an entity, it still returns the key for that entity but omits the 'value' key, while retaining the 'score' key to indicate confidence that the answer is not present. For example, the "buyer_name' field in Source demonstrates this by showing a 'score' but no 'value'
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