Designed notebook workflow for model diagnostics

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Designed notebook workflow for model diagnostics

  • Day: 2026-06-09
  • Time: 11:40 to 11:50
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Notebooks, Model-Diagnostics, Workflow, Parameterization, Geospatial-Effects, Regularization

Description

Session Goal

Define a notebook-first analysis workflow that supports decision-making for model diagnostics without contaminating the production backend.

Key Activities

  • Reframed the main bottleneck as friction between experiment outputs, human inspection, and downstream decisions.
  • Proposed notebooks as a temporary diagnostic layer with explicit boundaries from backend code.
  • Recommended working from clean, analysis-ready datasets rather than scattered files inside notebooks.
  • Designed a reusable notebook scaffold with parameterized inputs such as RUN_ID, EXPERIMENT_ID, and model names to avoid hard-coded paths.
  • Outlined a three-layer architecture: production backend, exploratory notebooks, and thesis-ready artifacts.
  • Specified a shared utility/loading layer for standardized ingestion of runs, predictions, residuals, CV outputs, and feature metadata.
  • Defined notebook roles for residual/compression analysis, geospatial/fixed-effect interpretation, and Ridge/Lasso regularization diagnostics.

Achievements

  • Clarified a modular research workflow for income prediction and interpretability analysis.
  • Established a notebook bootstrap pattern with separate ingestion and derived-data cells.
  • Identified the key artifact types and helper functions needed for reproducible diagnostics.
  • Set a rule that only stable insights should migrate back into the backend.

Pending Tasks

  • Implement the shared utility module for loading archived runs and diagnostics.
  • Create the three analysis notebooks using the proposed scaffold.
  • Add an audit script to verify required artifacts across runs.
  • Validate the geospatial/fixed-effect and regularization workflows on real experiment bundles.

Evidence

  • source_file=2026-06-09.sessions.jsonl, line_number=4, event_count=0, session_id=490c0ee5bad4ec4e0a2433ca82106e2119118167e9c0e6561b0a95a3e26a7b6b
  • event_ids: []

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