docs: English README with searchable title

README.md

@@ -1,27 +1,142 @@
----
-title: LEADBOARD
-emoji: 🎯
-colorFrom: blue
-colorTo: gray
-sdk: docker
-app_port: 7860
-# hf_oauth 를 켜야 플랫폼이 OAUTH_CLIENT_ID/SECRET 를 컨테이너에 넣어준다.
-hf_oauth: true
-pinned: false
-short_description: One yardstick for drug prediction tools
-tags:
-  - drug-discovery
-  - admet
-  - leaderboard
-  - benchmark
-  - cheminformatics
----
-
-# LEADBOARD
-
-신약 예측 도구를, 분야별로, 같은 잣대로 잰다.
-
-정답은 배포하지 않는다. 대신 채점자가 먼저 공개한다 —
-아무것도 학습하지 않은 기준선, 그 분야의 실험 잡음 바닥, 점수마다의 데이터·채점기 지문.
-
-규격 v1.1 (8개 조항) · FINAL-Bench / VIDRAFT
+---
+title: LEADBOARD - ADMET, Kinase and Toxicity Prediction Benchmark
+emoji: 🎯
+colorFrom: blue
+colorTo: gray
+sdk: docker
+app_port: 7860
+# hf_oauth 를 켜야 플랫폼이 OAUTH_CLIENT_ID/SECRET 를 컨테이너에 넣어준다.
+hf_oauth: true
+pinned: false
+short_description: Benchmark for drug prediction tools - ADMET, kinase, tox
+tags:
+  - drug-discovery
+  - admet
+  - leaderboard
+  - benchmark
+  - cheminformatics
+  - molecular-property-prediction
+  - qsar
+  - toxicity
+  - herg
+  - solubility
+  - kinase
+  - chembl
+  - cell-painting
+  - preclinical
+---
+
+# LEADBOARD
+
+**A benchmark for drug property prediction tools.** One yardstick, one discipline at a time.
+
+Submit predictions for a held-out set of molecules. We score them against labels
+we never release, and place your tool on the board for that discipline.
+
+👉 **[Open the leaderboard](https://huggingface.co/spaces/FINAL-Bench/leadboard)**
+
+---
+
+## What is measured
+
+Most published benchmarks split their molecules at random. That is the wrong
+question. A tool is used to rank compounds nobody has measured yet, so the honest
+test is: *train on what was known by a cut-off year, predict what came after.*
+
+We ran both splits on identical data with an identical model. On the hERG
+cardiotoxicity board, AUROC was **0.818** under a random split and **0.606** under
+a time split. Same molecules, same code — only the question changed. Every board
+here uses the harder one.
+
+## What we publish before you submit
+
+For each board, before any entry arrives:
+
+| Published | Why it matters |
+|---|---|
+| **Untrained baselines** | Constant prediction, nearest neighbour, Morgan+LightGBM. If a tool cannot beat these, the board says so. |
+| **Experimental noise floor** | How far apart two labs land when they measure the same compound. Nothing can be measured below it. |
+| **Split grade and answer grade** | Exactly how the test set was cut, and whether the labels can be looked up anywhere. |
+| **Data and scorer fingerprints** | The SHA of the exact test file and scoring code behind every score. |
+
+A score without its noise floor is a number without a unit. Both are shown.
+
+## Grading notation
+
+Each board carries two letters, for example `[T/P2]`.
+
+**Split grade** — what the board asks of a tool
+- `T` time split by first-report year
+- `S` scaffold split by Murcko core
+- `R` random split (we do not open these)
+
+**Answer grade** — whether an entrant can look the answer up
+- `P1` public source, our curation
+- `P2` public source, our unit conversion and selection define this revision
+- `P3` labels held privately
+- `P4` prospective — the answer does not exist yet
+
+## Boards
+
+21 boards across 7 disciplines, 18,382 held-out compounds.
+
+- 🫗 **Absorption** — Solubility
+- 🔥 **Metabolism** — CYP3A4, CYP2D6, CYP2C9
+- ☠️ **Toxicity** — hERG
+- 🎯 **Potency** — AChE, MAOB, COX2
+- 🔑 **Kinase** — EGFR, JAK2, PI3Kα, FLT3, VEGFR2, CDK2, HER2, ABL1, BRAF, KIT, ALK
+- 🔬 **Cell / Phenotype** — JUMP Cell Painting morphology, 115,689 compounds, 16 profile axes
+- 🏥 **Clinical** — Post-marketing withdrawal, year-matched controls
+
+The withdrawal board is worth a note. Withdrawal rate tracks approval decade
+(7.8% in the 1990s, 1.2% in the 2010s), so a predictor that reads nothing but the
+approval year scores AUROC 0.636. After year-matching the controls it scores 0.504
+— chance. That is the version we opened.
+
+## How to enter
+
+1. Pick a board and download its test set — structures only, no labels.
+2. Predict with your own tool. Anything goes: a trained model, a physics engine,
+   a language model, a rule of thumb.
+3. Upload a CSV of `compound_id,prediction`. Sign in with your Hugging Face account.
+4. Scoring runs off-platform on hardware that holds the labels. The Space never
+   sees them.
+
+The Space carries a filled-in prompt and a runnable skeleton for each board, so a
+first entry does not require building anything from scratch.
+
+### Repeated submissions
+
+New scores are revealed under the ladder rule (Blum & Hardt, ICML 2015): a fresh
+score replaces your best only when it beats it by more than the noise floor.
+Otherwise your previous best stands. This is what stops a leaderboard from being
+won by whoever submits the most times.
+
+## Data and licences
+
+- **ChEMBL 37** (EMBL-EBI) — CC BY-SA 3.0. Re-curated; attribution travels with every board card.
+- **JUMP Cell Painting Consortium** — CC0.
+- Withdrawal board assembled from public regulatory records.
+
+Non-commercial research benchmark. Test sets carry structures only; labels are
+never distributed.
+
+---
+
+## 한국어 요약
+
+**신약 예측 도구를, 분야별로, 같은 잣대로 잽니다.**
+
+정답은 배포하지 않습니다. 대신 채점자가 먼저 공개합니다 — 아무것도 학습하지 않은
+기준선, 그 분야의 실험 잡음 바닥, 점수마다의 데이터·채점기 지문.
+
+무작위 분할은 틀린 질문입니다. 도구는 아직 아무도 재지 않은 화합물의 순위를 매기는
+데 쓰이니, 정직한 시험은 **어느 해까지 알려진 것으로 배우고 그 뒤에 나온 것을
+맞히는 것**입니다. 같은 자료·같은 모델로 재 보면 hERG 심장독성 AUROC 가 무작위
+분할 0.818, 시간 분할 0.606 이었습니다. 여기 부문은 전부 어려운 쪽을 씁니다.
+
+7개 분야 21부문 · 테스트 화합물 18,382. 화면은 한국어·영어를 자동으로 가릅니다.
+
+---
+
+규격 v1.1 (8개 조항) · **FINAL-Bench / VIDRAFT**