# North Hoboken family map — delivery note

Open **`index.html`** by double-clicking it. There is no build step, local server, account, or API key. An internet connection is needed only for the Leaflet library, OpenStreetMap tiles, and outbound place links; all recommendations and scores are embedded in the HTML and still appear as a list if map tiles cannot load.

The guide includes 25 researched picks across playgrounds, family food, activities, day trips, date night, and a dedicated tapas category. It supports category/search filtering, favorites saved in the browser, geolocation-based distance sorting, map/list selection, directions, official links, score sorting, and a “60+ gems” filter.

## Hidden-gem result

The definitive methodology and six expectations were locked and hashed before the rating/review-count snapshot was collected. The prospective test **passed**:

- 5 of 6 locked expectations matched (83.3%);
- both calibration anchors passed;
- all 14 eligible observations were complete;
- all four preregistered robustness variants passed.

The top scores were Hoboken Historical Museum (76.2), The Gravity Vault (75.0), and Fiore’s (61.6). Fiore’s was the one prediction miss: its exceptional rating outweighed its very high visibility, and that miss was retained rather than tuning the formula.

## Inspectable deliverables

- `index.html` — double-clickable interactive map with embedded place and score data
- `places.json` — complete recommendation data, links, coordinates, and scoring eligibility
- `METHODOLOGY.md` — definitive preregistration (SHA-256 `1a7cc274eaeea24393e3f588830fdb653902126e116d384f168c26247612fdc7`)
- `PREREGISTRATION_LOG.md` — timing, hash, and preserved invalidated pilot record
- `score_inputs.json` — public review observations and direct source URLs
- `score_hidden_gems.py` — deterministic, standard-library scoring and validation script
- `scores.csv` / `scores.json` — computed ranks and all score components
- `VALIDATION.md` — prospective prior tests, acceptance criteria, and robustness results
- `SOURCES.md` — public place research and score-source ledger

To reproduce the score outputs, optionally run `python3 score_hidden_gems.py`; this is not needed to use the map.