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Copy file name to clipboardExpand all lines: docs/dyn/aiplatform_v1.projects.locations.batchPredictionJobs.html
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"resourcesConsumed": { # Statistics information about resource consumption. # Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models.
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"replicaHours": 3.14, # Output only. The number of replica hours used. Note that many replicas may run in parallel, and additionally any given work may be queued for some time. Therefore this value is not strictly related to wall time.
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},
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"serviceAccount": "A String", # The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.
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"startTime": "A String", # Output only. Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.
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"state": "A String", # Output only. The detailed state of the job.
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"resourcesConsumed": { # Statistics information about resource consumption. # Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models.
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"replicaHours": 3.14, # Output only. The number of replica hours used. Note that many replicas may run in parallel, and additionally any given work may be queued for some time. Therefore this value is not strictly related to wall time.
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},
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"serviceAccount": "A String", # The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.
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"startTime": "A String", # Output only. Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.
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"state": "A String", # Output only. The detailed state of the job.
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"resourcesConsumed": { # Statistics information about resource consumption. # Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models.
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"replicaHours": 3.14, # Output only. The number of replica hours used. Note that many replicas may run in parallel, and additionally any given work may be queued for some time. Therefore this value is not strictly related to wall time.
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},
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"serviceAccount": "A String", # The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.
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"startTime": "A String", # Output only. Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.
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"state": "A String", # Output only. The detailed state of the job.
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"resourcesConsumed": { # Statistics information about resource consumption. # Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models.
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"replicaHours": 3.14, # Output only. The number of replica hours used. Note that many replicas may run in parallel, and additionally any given work may be queued for some time. Therefore this value is not strictly related to wall time.
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},
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"serviceAccount": "A String", # The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.
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"startTime": "A String", # Output only. Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.
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"state": "A String", # Output only. The detailed state of the job.
Copy file name to clipboardExpand all lines: docs/dyn/aiplatform_v1.projects.locations.datasets.dataItems.html
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},
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"name": "A String", # Output only. The resource name of the DataItem.
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"payload": "", # Required. The data that the DataItem represents (for example, an image or a text snippet). The schema of the payload is stored in the parent Dataset's metadata schema's dataItemSchemaUri field.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"updateTime": "A String", # Output only. Timestamp when this DataItem was last updated.
Copy file name to clipboardExpand all lines: docs/dyn/aiplatform_v1.projects.locations.datasets.datasetVersions.html
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"metadata": "", # Required. Output only. Additional information about the DatasetVersion.
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"modelReference": "A String", # Output only. Reference to the public base model last used by the dataset version. Only set for prompt dataset versions.
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"name": "A String", # Output only. Identifier. The resource name of the DatasetVersion.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"updateTime": "A String", # Output only. Timestamp when this DatasetVersion was last updated.
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}
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"metadata": "", # Required. Output only. Additional information about the DatasetVersion.
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"modelReference": "A String", # Output only. Reference to the public base model last used by the dataset version. Only set for prompt dataset versions.
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"name": "A String", # Output only. Identifier. The resource name of the DatasetVersion.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"updateTime": "A String", # Output only. Timestamp when this DatasetVersion was last updated.
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}</pre>
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</div>
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"metadata": "", # Required. Output only. Additional information about the DatasetVersion.
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"modelReference": "A String", # Output only. Reference to the public base model last used by the dataset version. Only set for prompt dataset versions.
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"name": "A String", # Output only. Identifier. The resource name of the DatasetVersion.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"updateTime": "A String", # Output only. Timestamp when this DatasetVersion was last updated.
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},
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],
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"metadata": "", # Required. Output only. Additional information about the DatasetVersion.
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"modelReference": "A String", # Output only. Reference to the public base model last used by the dataset version. Only set for prompt dataset versions.
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"name": "A String", # Output only. Identifier. The resource name of the DatasetVersion.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"updateTime": "A String", # Output only. Timestamp when this DatasetVersion was last updated.
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}
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"metadata": "", # Required. Output only. Additional information about the DatasetVersion.
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"modelReference": "A String", # Output only. Reference to the public base model last used by the dataset version. Only set for prompt dataset versions.
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"name": "A String", # Output only. Identifier. The resource name of the DatasetVersion.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"updateTime": "A String", # Output only. Timestamp when this DatasetVersion was last updated.
Copy file name to clipboardExpand all lines: docs/dyn/aiplatform_v1.projects.locations.datasets.html
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"metadataSchemaUri": "A String", # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
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"modelReference": "A String", # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
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"name": "A String", # Output only. Identifier. The resource name of the Dataset.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"savedQueries": [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
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{ # A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
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"annotationFilter": "A String", # Output only. Filters on the Annotations in the dataset.
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"metadataSchemaUri": "A String", # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
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"modelReference": "A String", # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
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"name": "A String", # Output only. Identifier. The resource name of the Dataset.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"savedQueries": [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
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{ # A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
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"annotationFilter": "A String", # Output only. Filters on the Annotations in the dataset.
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"metadataSchemaUri": "A String", # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
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"modelReference": "A String", # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
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"name": "A String", # Output only. Identifier. The resource name of the Dataset.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"savedQueries": [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
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{ # A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
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"annotationFilter": "A String", # Output only. Filters on the Annotations in the dataset.
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"metadataSchemaUri": "A String", # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
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"modelReference": "A String", # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
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"name": "A String", # Output only. Identifier. The resource name of the Dataset.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"savedQueries": [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
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{ # A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
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"annotationFilter": "A String", # Output only. Filters on the Annotations in the dataset.
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"metadataSchemaUri": "A String", # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
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"modelReference": "A String", # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
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"name": "A String", # Output only. Identifier. The resource name of the Dataset.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"savedQueries": [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
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{ # A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
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"annotationFilter": "A String", # Output only. Filters on the Annotations in the dataset.
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},
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"name": "A String", # Output only. The resource name of the DataItem.
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"payload": "", # Required. The data that the DataItem represents (for example, an image or a text snippet). The schema of the payload is stored in the parent Dataset's metadata schema's dataItemSchemaUri field.
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"satisfiesPzi": True or False, # Output only. Reserved for future use.
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"satisfiesPzs": True or False, # Output only. Reserved for future use.
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"updateTime": "A String", # Output only. Timestamp when this DataItem was last updated.
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},
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"hasTruncatedAnnotations": True or False, # True if and only if the Annotations field has been truncated. It happens if more Annotations for this DataItem met the request's annotation_filter than are allowed to be returned by annotations_limit. Note that if Annotations field is not being returned due to field mask, then this field will not be set to true no matter how many Annotations are there.
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