Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
1Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5078072006
ORCID evidence
Observed aliases (4)
- Elsa de la Calleja (openalex, provider refresh)
- Elsa de la Calleja (openalex, source metadata)
- Elsa Marias De LA Calleja Mora (openalex, provider refresh)
- Elsa Marias De LA Calleja Mora (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Productivity: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Error Rate: 1 paper
- Task Completion Time: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| A retrieval-augmented LLM slashes engineers' proposal information-processing time by roughly 90% and produced no expert-detected hallucinations in domain tests, promising large per-cycle cost savings — though findings rest on a small, sector-specific experiment.openalex | Elsa Marias De LA Calleja Mora provider id |
2026-09-16 | 0 |
Citation observation summary
OpenAlex supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.