Source identity
| Field | Recorded value |
|---|---|
| Source type | GitHub source |
| Original record | Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json |
| Date | Not specified in source |
| Repository | Janady13/missionmatch |
| Revision | 720d47fae476b0d38477ae4401697d372b1ea2bc |
| Branch | feature/opportunity-to-outcome |
| Path or archive member | internal/integration/testdata/retrieval_qrels.json |
| Original SHA-256 | 9495714f33f9df37fd2ba9833026c06fb380115e7b086baec9dbbd6293c484d3 |
| Git blob SHA | 94069dccd3602410769f08e2dc59d715c3293b7c |
| Reading-copy SHA-256 | 9495714f33f9df37fd2ba9833026c06fb380115e7b086baec9dbbd6293c484d3 |
Every recorded occurrence
These 12 records contain identical original source bytes. Their paths and revisions remain part of the archive.
| Original record | Branch or archive | Revision / identifier | Original location |
|---|---|---|---|
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | feature/opportunity-to-outcome | 720d47fae476b0d38477ae4401697d372b1ea2bc | Open original |
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | collision-deconfliction | 4ee5a09972608ed89f8377c6665542d5f450f0a6 | Open original |
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | m5-price-to-win | 41000ad30fff4129fdaf5ec84e15ba14c27d4890 | Open original |
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | master | 1e9249840a4302ec82e123b9c9cb6f75badea3e4 | Open original |
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | mag-substrate | b82c7100a492dec67dfd1eda6b3f53def859be35 | Open original |
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | time-to-fill-survival | b66e1e505863d4f17741a4b9ede73509e45bd6c6 | Open original |
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | graphrag-foundation | b0ddeb9f633fd138d09309d1a17b7d13bc3a67f7 | Open original |
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | presentation-readiness | eb574acaa29d71ce4d0f852572e87c275c79fdb7 | Open original |
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | vendor-intelligence | fe9796a19c261951d3f2565206c0c1b5ac294465 | Open original |
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | phase2-connectors | e038d4c687aec16f8bd9bc4d907eea14d91f8704 | Open original |
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | feature/aioe-upgrade | 2178e7298d0e5d9af83afa12402fd587f0ba6ed8 | Open original |
| Janady13/missionmatch / internal/integration/testdata/retrieval_qrels.json | capture-readiness | bae6af7cb2997e819174a9e9cfff5e16067a1975 | Open original |
Recovered source transcript
Download complete source text ↓147 lines · 6.2 KB
{
"_about": "Versioned retrieval regression gold set (qrels) for the missionMATCH hybrid search. This is the judgment fixture the recall at k, MRR, and nDCG harness scores the live RRF HybridSearch against. It is a REGRESSION GATE: a correct hybrid search must clear the floors in retrieval_recall_integration_test.go comfortably, and a real regression in embeddings, HNSW tuning, the mission gate, or the RRF k constant should drop a metric below a floor. Each candidate carries a stable seed key (a distinctive term that appears in its full text), NOT a random uuid, so the harness seeds the exact candidate and maps a returned CandidateID back to its key. Each query lists the seed keys judged relevant to it. To extend: add a candidate with a new unique seed key and a realistic cleared workforce full text, add or update a query whose relevant list names the keys that SHOULD come back, bump the version, and confirm the new query still clears the floors with the real embedding plane (MM_MEGAMIND_URL set). Keep the relevant set findable: the relevant candidates full text must contain the query terms (the full text leg) and be semantically near the query (the vector leg).",
"version": "1.0.0",
"candidates": [
{
"key": "cryptanalysis_sigint",
"full_name": "Avery Cole",
"clearance_level": "top_secret",
"clearance_poly": "full_scope",
"clearance_status": "active",
"location": "Fort Meade, Maryland",
"headline": "Senior cryptanalysis and SIGINT collection lead with TS SCI full scope polygraph clearance"
},
{
"key": "intel_analyst_allsource",
"full_name": "Bria Donovan",
"clearance_level": "top_secret",
"clearance_poly": "ci",
"clearance_status": "active",
"location": "Honolulu, Hawaii",
"headline": "All source intelligence analyst, threat assessment and targeting, TS SCI active clearance"
},
{
"key": "intel_analyst_geospatial",
"full_name": "Cody Erskine",
"clearance_level": "top_secret",
"clearance_poly": "none",
"clearance_status": "active",
"location": "Honolulu, Hawaii",
"headline": "Geospatial intelligence analyst, imagery exploitation and GEOINT production, TS SCI cleared"
},
{
"key": "cloud_security_aws",
"full_name": "Dana Fitzgerald",
"clearance_level": "secret",
"clearance_poly": "none",
"clearance_status": "active",
"location": "Albuquerque, New Mexico",
"headline": "Cloud security engineer, AWS GovCloud, Kubernetes and incident response, Secret clearance"
},
{
"key": "cyber_architect_zerotrust",
"full_name": "Elio Garrett",
"clearance_level": "top_secret",
"clearance_poly": "none",
"clearance_status": "active",
"location": "Albuquerque, New Mexico",
"headline": "Cyber security architect, zero trust and network defense design for cloud platforms, TS cleared"
},
{
"key": "data_scientist_ml",
"full_name": "Faye Holloway",
"clearance_level": "secret",
"clearance_poly": "none",
"clearance_status": "active",
"location": "Honolulu, Hawaii",
"headline": "Data scientist, machine learning and Python modeling for mission analytics, Secret clearance"
},
{
"key": "network_engineer_cisco",
"full_name": "Gunnar Iverson",
"clearance_level": "secret",
"clearance_poly": "none",
"clearance_status": "active",
"location": "San Antonio, Texas",
"headline": "Network engineer, Cisco routing and switching and SD WAN for tactical communications"
},
{
"key": "linguist_arabic",
"full_name": "Hana Juarez",
"clearance_level": "top_secret",
"clearance_poly": "ci",
"clearance_status": "active",
"location": "Fort Meade, Maryland",
"headline": "Arabic cryptologic linguist, transcription and translation for SIGINT, TS SCI cleared"
},
{
"key": "program_manager_capture",
"full_name": "Ivo Kowalski",
"clearance_level": "secret",
"clearance_poly": "none",
"clearance_status": "active",
"location": "Honolulu, Hawaii",
"headline": "Program manager and capture lead for federal contracts, PMP certified, Secret clearance"
},
{
"key": "software_engineer_golang",
"full_name": "Jules Marchetti",
"clearance_level": "secret",
"clearance_poly": "none",
"clearance_status": "active",
"location": "San Antonio, Texas",
"headline": "Software engineer, Go and Postgres backend services for secure platforms, Secret clearance"
},
{
"key": "devops_kubernetes",
"full_name": "Kira Novak",
"clearance_level": "secret",
"clearance_poly": "none",
"clearance_status": "active",
"location": "Albuquerque, New Mexico",
"headline": "DevOps engineer, Kubernetes and Terraform automation on AWS GovCloud, Secret clearance"
},
{
"key": "helpdesk_tier1",
"full_name": "Lena Ortega",
"clearance_level": "none",
"clearance_poly": "none",
"clearance_status": "unknown",
"location": "Clarksville, Tennessee",
"headline": "Tier one help desk technician, ticketing and end user support, no active clearance"
}
],
"queries": [
{
"id": "q_sigint_cryptanalysis",
"text": "cryptanalysis and SIGINT collection specialist",
"relevant": ["cryptanalysis_sigint", "linguist_arabic"]
},
{
"id": "q_intel_analyst",
"text": "intelligence analyst",
"relevant": ["intel_analyst_allsource", "intel_analyst_geospatial"]
},
{
"id": "q_cloud_security",
"text": "cloud security engineer AWS GovCloud",
"relevant": ["cloud_security_aws", "cyber_architect_zerotrust", "devops_kubernetes"]
},
{
"id": "q_data_scientist",
"text": "data scientist machine learning Python",
"relevant": ["data_scientist_ml"]
},
{
"id": "q_software_engineer_go",
"text": "Go software engineer backend services",
"relevant": ["software_engineer_golang"]
},
{
"id": "q_capture_program_manager",
"text": "program manager capture lead federal contracts",
"relevant": ["program_manager_capture"]
}
]
}