ca4a54181e
- Updated WorldCatIdentifier.yaml to remove unnecessary description and ensure consistent formatting. - Enhanced WorldHeritageSite.yaml by breaking long description into multiple lines for better readability and removed unused attributes. - Simplified WritingSystem.yaml by removing redundant attributes and ensuring consistent formatting. - Cleaned up XPathScore.yaml by removing unnecessary attributes and ensuring consistent formatting. - Improved YoutubeChannel.yaml by breaking long description into multiple lines for better readability. - Enhanced YoutubeEnrichment.yaml by breaking long description into multiple lines for better readability. - Updated YoutubeVideo.yaml to break long description into multiple lines and removed legacy field name. - Refined has_or_had_affiliation.yaml by removing unnecessary comments and ensuring clarity. - Cleaned up is_or_was_retrieved_at.yaml by removing unnecessary comments and ensuring clarity. - Added rules for generic slots and avoiding rough edits in schema files to maintain structural integrity. - Introduced changes_or_changed_through.yaml to define a new slot for linking entities to change events.
96 lines
No EOL
4.1 KiB
YAML
96 lines
No EOL
4.1 KiB
YAML
id: https://nde.nl/ontology/hc/class/DetectionThreshold
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name: DetectionThreshold
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title: Detection Threshold Class
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prefixes:
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linkml: https://w3id.org/linkml/
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hc: https://nde.nl/ontology/hc/
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dqv: http://www.w3.org/ns/dqv#
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schema: http://schema.org/
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prov: http://www.w3.org/ns/prov#
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dcterms: http://purl.org/dc/terms/
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crm: http://www.cidoc-crm.org/cidoc-crm/
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skos: http://www.w3.org/2004/02/skos/core#
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rdfs: http://www.w3.org/2000/01/rdf-schema#
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org: http://www.w3.org/ns/org#
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xsd: http://www.w3.org/2001/XMLSchema#
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default_prefix: hc
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imports:
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- linkml:types
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- ../metadata
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- ../slots/has_or_had_description
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- ../slots/has_or_had_label
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- ../slots/has_or_had_type
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classes:
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DetectionThreshold:
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class_uri: dqv:QualityMeasurement
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description: "Configuration for detection thresholds in analysis pipelines.\n\n**DEFINITION**:\n\nDetectionThreshold represents the confidence threshold settings used to filter\ndetection results. CV models output confidence scores; thresholds determine\nwhich detections are included in results.\n\n**Threshold Levels**:\n\n| Threshold | Range | Use Case |\n|-----------|-------|----------|\n| HIGH_PRECISION | 0.9+ | Production display, high confidence |\n| BALANCED | 0.7-0.9 | General use, balance precision/recall |\n| HIGH_RECALL | 0.5-0.7 | Research, review, catch more |\n| RAW | < 0.5 | Unfiltered, needs post-processing |\n\n**Ontological Alignment**:\n- **DQV**: `dqv:QualityMeasurement` - quality metric for data assessment\n- **PROV-O**: Threshold as parameter of detection activity\n\n**Migrated From** (per slot_fixes.yaml):\n- `detection_threshold` (float) now uses:\n - `filters_or_filtered` \u2192 DetectedEntity\n - `has_or_had_treshold` \u2192 DetectionThreshold (this class)\n\
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\n**Usage Pattern**:\n```\nVideoAnnotation\n \u2514\u2500\u2500 filters_or_filtered \u2192 DetectedEntity\n \u2514\u2500\u2500 has_or_had_treshold \u2192 DetectionThreshold\n \u251C\u2500\u2500 threshold_value: 0.5\n \u2514\u2500\u2500 threshold_type: MINIMUM\n```\n"
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exact_mappings:
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- dqv:QualityMeasurement
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close_mappings:
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- schema:QuantitativeValue
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related_mappings:
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- prov:SoftwareAgent
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slots:
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- has_or_had_label
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- has_or_had_description
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- has_or_had_type
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attributes:
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threshold_value:
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range: float
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required: true
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minimum_value: 0.0
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maximum_value: 1.0
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description: 'The numeric threshold value (0.0-1.0).
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Detections with confidence >= threshold_value are included.
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'
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examples:
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- value: 0.5
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description: Standard threshold
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- value: 0.9
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description: High precision threshold
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threshold_type:
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range: string
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required: false
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description: 'Type of threshold application.
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- MINIMUM: Lower bound for inclusion
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- MAXIMUM: Upper bound (rare)
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- BAND: Range between two values
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'
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examples:
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- value: MINIMUM
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description: Minimum confidence for inclusion
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slot_usage:
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has_or_had_label:
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examples:
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- value: High Precision Threshold
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- value: Research Mode Threshold
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has_or_had_type:
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examples:
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- value: HIGH_PRECISION
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- value: BALANCED
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annotations:
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custodian_types: '["D"]'
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custodian_types_rationale: Detection thresholds apply to digital platforms with automated analysis
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specificity_score: 0.75
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specificity_rationale: Fairly specific to video/media analysis contexts
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comments:
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- Represents detection threshold configuration
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- Migrated from detection_threshold slot per slot_fixes.yaml
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- threshold_value is the numeric confidence cutoff
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- threshold_type indicates how threshold is applied
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examples:
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- value:
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has_or_had_label: Standard Detection
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- value:
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has_or_had_label: High Precision
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has_or_had_description: For production display requiring high confidence
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- value:
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has_or_had_label: Research Mode
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has_or_had_description: Low threshold to maximize recall for research |