114 lines
4.5 KiB
Markdown
114 lines
4.5 KiB
Markdown
# Utah Vehicle Health dashboard demo script
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Target length: **2 minutes 45 seconds**, embedded in the
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[10-minute presentation](presentation_outline.md).
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## Before the audience arrives
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1. From the repository root, run `node dashboard/server.mjs`.
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2. Open `http://127.0.0.1:4173/#overview`.
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3. Confirm the header says the sample aggregates validated.
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4. Confirm the private-sample development-preview banner is visible.
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5. Visit all four routes: Overview, Sample cohorts, Model & benchmark, and Data
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& methods.
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6. Reset Sample cohorts and leave its sort on largest support.
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Do not open developer tools, private files, model artifacts, database clients,
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or environment variables during the presentation.
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## Live talk track
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### 0:00-0:25 — Establish the boundary
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**Action:** Start on **Overview**. Point to the development-preview banner before
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pointing to a chart.
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**Say:**
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> The most important element is this banner. Every value in the dashboard comes
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> from the private 10,000-vehicle development sample. These are suppression-
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> reviewed sample aggregates, not population estimates, and they cannot support
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> individual decisions or county rankings.
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### 0:25-1:00 — Explain the overview
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**Action:** Point to published support and the observed first-attempt non-pass
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trend, then the coverage map and vehicle-age chart. Do not rank counties by
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outcome.
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**Say:**
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> The overview reports rounded support and sample first-attempt outcomes for
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> returning vehicles. Non-pass combines fail, reject, and abort. The trend is
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> descriptive of sampled records only. This county graphic communicates feed
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> availability: gray means unavailable, not zero and not better. The age pattern
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> is also an observed sample association, not a causal claim or diagnosis.
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### 1:00-1:35 — Use Sample cohorts safely
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**Action:** Open **Sample cohorts**. Search for `Toyota` or another currently
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supported make. Leave sorting on largest support. Point to rounded support and
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the “observed sample non-pass” label.
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**Say:**
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> This view contains only prior make-and-model cohorts that cleared the
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> publication thresholds. I can search supported cohorts, but these are observed
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> development-sample associations—not reliability grades, rankings, or
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> recommendations. Unsupported slices are not inferred in the browser, and
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> suppressed rows are absent rather than hidden.
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**Action:** Reset the search before leaving the view.
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### 1:35-2:15 — Separate the final model from its benchmark
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**Action:** Open **Model & benchmark**. Point first to the role badges, then the
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2024 calibration-fit scope strip, then the “No vehicle-level prediction service”
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boundary.
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**Say:**
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> The governance decision is explicit: calibrated logistic regression is the
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> final prototype model, while the boosted tree is benchmark-only. The numbers
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> shown here are pre-2025 checks on the same 2024 sample partition used to fit
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> calibration. They are not independent final-performance or population
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> estimates, so we do not select between the cards from these values. The
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> one-time 2025 comparison shown earlier favored logistic and stays in the report
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> and presentation, not the browser bundle. This finished dashboard contains no
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> vehicle lookup, personal inputs, or row-level prediction output.
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### 2:15-2:40 — Close on method and privacy
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**Action:** Open **Data & methods**. Briefly point to Prediction unit, the
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chronological timeline, evidence status, and the privacy flow.
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**Say:**
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> The method page makes the contract visible: the target is the first attempt of
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> a returning vehicle's next episode, and every feature ends before that episode.
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> Training, tuning, and calibration are chronological. It also records that 2025
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> was opened once after choices were frozen. Finally, the public path ends in
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> suppressed summaries. No private rows or database connection reach this site.
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### 2:40-2:45 — Transition
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**Say:**
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> That is the prototype: useful sample evidence, with model and privacy
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> boundaries kept visible.
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Return to the slide deck's privacy architecture.
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## If something goes wrong
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If the dashboard shows **data unavailable**, do not bypass validation or edit
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JSON. Say:
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> The site rejected an aggregate-contract mismatch and is failing closed, so it
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> shows no estimates. That behavior is part of the privacy and integrity design.
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Then continue with a backup screenshot or slides. If a cohort search returns no
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rows, explain that unsupported or suppressed cohorts are intentionally absent
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and reset the filter. Never substitute remembered values or improvise a vehicle-
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level example.
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