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
0Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5070605462
ORCID evidence
Observed aliases (4)
- Félix Oscar Socorro Márquez (openalex, provider refresh)
- Félix Oscar Socorro Márquez (openalex, source metadata)
- Socorro Márquez, Félix Oscar (openalex, provider refresh)
- Socorro Márquez, Félix Oscar (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Training Effectiveness: 1 paper
- Adoption Rate: 1 paper
- Firm Revenue: 1 paper
- Governance And Regulation: 1 paper
- Organizational Efficiency: 1 paper
- Research Productivity: 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 |
|---|---|---|---|
| An AI-driven corporate learning model produced a 62% rise in knowledge retention and 88% module completion in a small pilot, and company-level ROI projections are extremely large — but the results rest on a non-randomized 48-person trial and assumption-heavy financial modeling.openalex | Socorro Márquez, Félix Oscar provider id |
2026-01-01 | 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.