Pith Number

pith:MWZTPDZJ

pith:2026:MWZTPDZJ6N2BDU6RYG7V2ILEDH

not attested not anchored not stored refs pending

Intelligent Truck Matching in Full Truckload Shipments using Ping2Hex approach

Ankit Singh Chauhan, Aravind Manoj, Dinesh Rajkumar, Jose Mathew, Mohit Goel, Srinivas Kumar Ramdas

Machine learning with H3 hexagonal GPS indexing matches trucks to shipments more accurately when vehicle IDs are missing.

arxiv:2605.07733 v2 · 2026-05-08 · cs.LG · cs.AI

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{MWZTPDZJ6N2BDU6RYG7V2ILEDH}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Through rigorous evaluation including offline model selection (SVM, XGBoost, LightGBM), comprehensive ablation studies, and production shadow testing, ITM 2.0 achieves 26 percentage point precision improvement in North America and 14 points in Europe, while doubling coverage.

C2weakest assumption

That historical matched shipment data provides a sufficiently clean and representative training signal, and that H3 discretization combined with temporal features can reliably distinguish correct matches despite geocoding errors up to 1 km and multiple candidate trucks.

C3one line summary

ITM 2.0 uses Uber H3 hexagons on GPS data plus temporal features with LightGBM ranking and threshold post-processing to match trucks to full truckload shipments, delivering 26 percentage point precision gains in North America and doubled coverage.

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-26T01:02:35.530167Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

65b3378f29f37411d3d1c1bf5d216419c081163e7ec7dc4c561b760528a3b0e3

Aliases

arxiv: 2605.07733 · arxiv_version: 2605.07733v2 · doi: 10.48550/arxiv.2605.07733 · pith_short_12: MWZTPDZJ6N2B · pith_short_16: MWZTPDZJ6N2BDU6R · pith_short_8: MWZTPDZJ

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/MWZTPDZJ6N2BDU6RYG7V2ILEDH \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 65b3378f29f37411d3d1c1bf5d216419c081163e7ec7dc4c561b760528a3b0e3

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "1f90f607987b60bd1c886e41bfe2bd1a444d85257e7cbfbda29c36b286be2a9f",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-08T13:40:53Z",
    "title_canon_sha256": "3989f43ed23f937958aec1169c135ededee8b71b4099cd5918462c14dfac46b3"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.07733",
    "kind": "arxiv",
    "version": 2
  }
}