Publish FUTURE-TS v0.1.0 public preview
Browse files- index.html +49 -6
- styles.css +74 -15
index.html
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@@ -111,16 +111,59 @@
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</div>
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<table class="board">
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<thead>
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<tr><th class="mono">Rank</th><th class="mono">Model</th><th class="mono num">Score</th></tr>
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</thead>
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<tbody>
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<tr><td class="rank mono">01</td><td>Datadog/Toto-2.0-1B</td><td class="num mono">0.2369</td></tr>
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<tr><td class="rank mono">02</td><td>Datadog/Toto-2.0-313m</td><td class="num mono">0.2214</td></tr>
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<tr><td class="rank mono">03</td><td>NX-AI/TiRex</td><td class="num mono">0.2024</td></tr>
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<tr><td class="rank mono">04</td><td>Salesforce/moirai-2.0-R-small</td><td class="num mono">0.1860</td></tr>
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<tr><td class="rank mono">05</td><td>amazon/chronos-2</td><td class="num mono">0.1851</td></tr>
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</tbody>
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</table>
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<div class="board-links">
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<a href="reports/tsfm_ai_empirical_v2_multi_budget/leaderboard.json">Leaderboard JSON</a>
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<a href="paper/future_ts_empirical.pdf">Empirical paper</a>
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</div>
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<table class="board">
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<thead>
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<tr><th class="mono">Rank</th><th class="mono">Model</th><th class="mono">Tier</th><th class="num mono">Score</th></tr>
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</thead>
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<tbody>
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<tr><td class="rank mono">01</td><td class="model">Datadog/Toto-2.0-1B</td><td class="tier mono">T1</td><td class="num mono">0.2369</td></tr>
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| 118 |
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<tr><td class="rank mono">02</td><td class="model">Datadog/Toto-2.0-313m <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T2</td><td class="num mono">0.2214</td></tr>
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<tr><td class="rank mono">03</td><td class="model">NX-AI/TiRex <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T3</td><td class="num mono">0.2024</td></tr>
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<tr><td class="rank mono">04</td><td class="model">Salesforce/moirai-2.0-R-small <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T4</td><td class="num mono">0.1860</td></tr>
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<tr><td class="rank mono">05</td><td class="model">amazon/chronos-2 <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T4</td><td class="num mono">0.1851</td></tr>
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<tr><td class="rank mono">06</td><td class="model">NX-AI/TiRex-1.1-gifteval</td><td class="tier mono">T4</td><td class="num mono">0.1833</td></tr>
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<tr><td class="rank mono">07</td><td class="model">google/timesfm-2.5-200m-pytorch</td><td class="tier mono">T4</td><td class="num mono">0.1772</td></tr>
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<tr><td class="rank mono">08</td><td class="model">google/timesfm-2.0-500m-pytorch <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T4</td><td class="num mono">0.1706</td></tr>
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<tr><td class="rank mono">09</td><td class="model">Datadog/Toto-2.0-22m</td><td class="tier mono">T4</td><td class="num mono">0.1640</td></tr>
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<tr><td class="rank mono">10</td><td class="model">Datadog/Toto-2.0-4m <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T4</td><td class="num mono">0.1557</td></tr>
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<tr><td class="rank mono">11</td><td class="model">cisco-ai/cisco-time-series-model-1.0 <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T5</td><td class="num mono">0.1437</td></tr>
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<tr><td class="rank mono">12</td><td class="model">Salesforce/moirai-1.1-R-large</td><td class="tier mono">T6</td><td class="num mono">0.1277</td></tr>
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<tr><td class="rank mono">13</td><td class="model">amazon/chronos-t5-large</td><td class="tier mono">T7</td><td class="num mono">0.1068</td></tr>
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<tr><td class="rank mono">14</td><td class="model">Salesforce/moirai-1.1-R-base</td><td class="tier mono">T7</td><td class="num mono">0.1067</td></tr>
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<tr><td class="rank mono">15</td><td class="model">amazon/chronos-bolt-mini</td><td class="tier mono">T7</td><td class="num mono">0.1030</td></tr>
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<tr><td class="rank mono">16</td><td class="model">Salesforce/moirai-1.1-R-small <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T8</td><td class="num mono">0.0882</td></tr>
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<tr><td class="rank mono">17</td><td class="model">mldi-lab/Kairos_50m</td><td class="tier mono">T9</td><td class="num mono">0.0746</td></tr>
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<tr><td class="rank mono">18</td><td class="model">ibm-research/granite-timeseries-flowstate-r1.1 <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T9</td><td class="num mono">0.0738</td></tr>
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<tr><td class="rank mono">19</td><td class="model">amazon/chronos-bolt-small</td><td class="tier mono">T9</td><td class="num mono">0.0645</td></tr>
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<tr><td class="rank mono">20</td><td class="model">thuml/sundial-base-128m</td><td class="tier mono">T9</td><td class="num mono">0.0618</td></tr>
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<tr><td class="rank mono">21</td><td class="model">Datadog/Toto-Open-Base-1.0</td><td class="tier mono">T9</td><td class="num mono">0.0574</td></tr>
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<tr><td class="rank mono">22</td><td class="model">amazon/chronos-bolt-base <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T9</td><td class="num mono">0.0518</td></tr>
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<tr><td class="rank mono">23</td><td class="model">mldi-lab/Kairos_23m</td><td class="tier mono">T9</td><td class="num mono">0.0464</td></tr>
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<tr><td class="rank mono">24</td><td class="model">Maple728/TimeMoE-50M <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T9</td><td class="num mono">0.0406</td></tr>
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<tr><td class="rank mono">25</td><td class="model">bytedance-research/Timer-S1</td><td class="tier mono">T9</td><td class="num mono">0.0369</td></tr>
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<tr><td class="rank mono">26</td><td class="model">Salesforce/moirai-1.0-R-large</td><td class="tier mono">T10</td><td class="num mono">0.0268</td></tr>
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<tr><td class="rank mono">27</td><td class="model">amazon/chronos-bolt-tiny <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T10</td><td class="num mono">0.0268</td></tr>
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| 144 |
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<tr><td class="rank mono">28</td><td class="model">Salesforce/moirai-1.0-R-base</td><td class="tier mono">T10</td><td class="num mono">0.0220</td></tr>
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| 145 |
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<tr><td class="rank mono">29</td><td class="model">NeoQuasar/Kronos-base</td><td class="tier mono">T10</td><td class="num mono">0.0207</td></tr>
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| 146 |
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<tr><td class="rank mono">30</td><td class="model">ibm-research/granite-timeseries-flowstate-r1</td><td class="tier mono">T10</td><td class="num mono">0.0176</td></tr>
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<tr><td class="rank mono">31</td><td class="model">Salesforce/moirai-1.0-R-small</td><td class="tier mono">T11</td><td class="num mono neg">-0.0331</td></tr>
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<tr><td class="rank mono">32</td><td class="model">Maple728/TimeMoE-200M <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T12</td><td class="num mono neg">-0.0452</td></tr>
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<tr><td class="rank mono">33</td><td class="model">qcw2333/YingLong_300m</td><td class="tier mono">T12</td><td class="num mono neg">-0.0546</td></tr>
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<tr><td class="rank mono">34</td><td class="model">mldi-lab/Kairos_10m</td><td class="tier mono">T12</td><td class="num mono neg">-0.0566</td></tr>
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<tr><td class="rank mono">35</td><td class="model">ibm-research/granite-timeseries-ttm-v1</td><td class="tier mono">T12</td><td class="num mono neg">-0.0648</td></tr>
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<tr><td class="rank mono">36</td><td class="model">ibm-research/granite-timeseries-ttm-r2 <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T13</td><td class="num mono neg">-0.1112</td></tr>
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<tr><td class="rank mono">37</td><td class="model">qcw2333/YingLong_110m <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T14</td><td class="num mono neg">-0.1403</td></tr>
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<tr><td class="rank mono">38</td><td class="model">qcw2333/YingLong_50m</td><td class="tier mono">T15</td><td class="num mono neg">-0.2224</td></tr>
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<tr><td class="rank mono">39</td><td class="model">qcw2333/YingLong_6m</td><td class="tier mono">T16</td><td class="num mono neg">-0.3691</td></tr>
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<tr><td class="rank mono">40</td><td class="model">time-series-foundation-models/Lag-Llama</td><td class="tier mono">T17</td><td class="num mono neg">-0.6597</td></tr>
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<tr><td class="rank mono">41</td><td class="model">ibm-research/ttm-r3 <span class="pareto" title="Pareto-optimal" aria-label="Pareto-optimal">β</span></td><td class="tier mono">T18</td><td class="num mono neg">-0.7236</td></tr>
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<tr><td class="rank mono">42</td><td class="model">Salesforce/moirai-moe-1.0-R-base</td><td class="tier mono">T19</td><td class="num mono neg">-1.0577</td></tr>
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<tr><td class="rank mono">43</td><td class="model">Salesforce/moirai-moe-1.0-R-small</td><td class="tier mono">T19</td><td class="num mono neg">-1.0644</td></tr>
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<tr><td class="rank mono">44</td><td class="model">AutonLab/MOMENT-1-large</td><td class="tier mono">T20</td><td class="num mono neg">-1.2300</td></tr>
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<tr><td class="rank mono">45</td><td class="model">ibm-research/granite-timeseries-patchtst-fm-r1</td><td class="tier mono">T21</td><td class="num mono neg">-1.6944</td></tr>
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<tr><td class="rank mono">46</td><td class="model">AutonLab/MOMENT-1-small</td><td class="tier mono">T22</td><td class="num mono neg">-7.0476</td></tr>
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<tr><td class="rank mono">47</td><td class="model">AutonLab/MOMENT-1-base</td><td class="tier mono">T23</td><td class="num mono neg">-1281.3842</td></tr>
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</tbody>
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</table>
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<p class="board-note mono"><span class="pareto-key">β</span> Pareto-optimal across budget & cost Β· tiers group models whose rank intervals overlap (not statistically separable).</p>
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<div class="board-links">
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<a href="reports/tsfm_ai_empirical_v2_multi_budget/leaderboard.json">Leaderboard JSON</a>
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<a href="paper/future_ts_empirical.pdf">Empirical paper</a>
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styles.css
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.stats div {
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border-right: 1px solid var(--line);
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padding: clamp(28px, 4vw, 44px) 0;
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}
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.stats div:last-child {
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border-right: 0;
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}
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.stat-num {
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/* ββ Leaderboard ββββββββββββββββββββββββββββββββββββββββββββ */
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.board {
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border-collapse: collapse;
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margin-top: clamp(
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width: 100%;
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}
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font-size: 11px;
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font-weight: 500;
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letter-spacing: 0.06em;
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padding: 0
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text-align: left;
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text-transform: uppercase;
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}
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.board td {
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border-bottom: 1px solid var(--line);
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font-size:
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padding:
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}
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.board tr:last-child td {
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border-bottom: 0;
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}
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.board
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}
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.board .rank {
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color: var(--ink-3);
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font-size:
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width:
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}
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.board tbody tr:first-child .rank {
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color: var(--accent-ink);
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}
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.board tbody tr:first-child
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}
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.board-links {
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.stats div:nth-child(-n + 2) {
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border-bottom: 1px solid var(--line);
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}
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.grid-4,
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.steps {
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grid-template-columns: 1fr;
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border-right: 0;
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padding-left: 0 !important;
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}
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}
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.board .rank {
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width:
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}
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}
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.stats div {
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border-right: 1px solid var(--line);
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padding: clamp(28px, 4vw, 44px) 28px clamp(28px, 4vw, 44px) 0;
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}
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.stats div:not(:first-child) {
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padding-left: 28px;
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}
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.stats div:last-child {
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border-right: 0;
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padding-right: 0;
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}
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.stat-num {
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/* ββ Leaderboard ββββββββββββββββββββββββββββββββββββββββββββ */
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.board {
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border-collapse: collapse;
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margin-top: clamp(28px, 3.5vw, 44px);
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width: 100%;
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}
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font-size: 11px;
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font-weight: 500;
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letter-spacing: 0.06em;
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padding: 0 14px 12px 0;
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text-align: left;
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text-transform: uppercase;
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}
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.board td {
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border-bottom: 1px solid var(--line);
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font-size: 13.5px;
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padding: 8px 14px 8px 0;
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}
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.board tr:last-child td {
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border-bottom: 0;
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}
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.board tbody tr {
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transition: background 120ms ease;
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}
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.board tbody tr:hover td {
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background: rgba(143, 70, 255, 0.04);
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}
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.board .rank {
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color: var(--ink-3);
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font-size: 12px;
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width: 48px;
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}
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.board .model {
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color: var(--ink);
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}
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.board .tier {
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color: var(--ink-3);
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font-size: 12px;
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width: 60px;
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}
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.board th.num,
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.board td.num {
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color: var(--ink);
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font-weight: 500;
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padding-right: 0;
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text-align: right;
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white-space: nowrap;
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width: 116px;
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}
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.board .num.neg {
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| 433 |
+
color: var(--ink-3);
|
| 434 |
+
font-weight: 400;
|
| 435 |
+
}
|
| 436 |
+
|
| 437 |
+
.board .pareto {
|
| 438 |
+
color: var(--accent);
|
| 439 |
+
font-size: 9px;
|
| 440 |
+
margin-left: 3px;
|
| 441 |
+
vertical-align: middle;
|
| 442 |
}
|
| 443 |
|
| 444 |
.board tbody tr:first-child .rank {
|
| 445 |
color: var(--accent-ink);
|
| 446 |
}
|
| 447 |
+
.board tbody tr:first-child .model,
|
| 448 |
+
.board tbody tr:first-child .num {
|
| 449 |
+
font-weight: 700;
|
| 450 |
+
}
|
| 451 |
+
|
| 452 |
+
.board-note {
|
| 453 |
+
color: var(--ink-3);
|
| 454 |
+
font-size: 11px;
|
| 455 |
+
letter-spacing: 0.02em;
|
| 456 |
+
line-height: 1.5;
|
| 457 |
+
margin: 14px 0 0;
|
| 458 |
+
}
|
| 459 |
+
.board-note .pareto-key {
|
| 460 |
+
color: var(--accent);
|
| 461 |
}
|
| 462 |
|
| 463 |
.board-links {
|
|
|
|
| 588 |
.stats div:nth-child(-n + 2) {
|
| 589 |
border-bottom: 1px solid var(--line);
|
| 590 |
}
|
| 591 |
+
.stats div:nth-child(odd) {
|
| 592 |
+
padding-left: 0;
|
| 593 |
+
}
|
| 594 |
+
.stats div:nth-child(even) {
|
| 595 |
+
padding-left: 28px;
|
| 596 |
+
padding-right: 0;
|
| 597 |
+
}
|
| 598 |
.grid-4,
|
| 599 |
.steps {
|
| 600 |
grid-template-columns: 1fr;
|
|
|
|
| 604 |
border-right: 0;
|
| 605 |
padding-left: 0 !important;
|
| 606 |
}
|
| 607 |
+
/* drop the secondary Tier column on small screens for legibility */
|
| 608 |
+
.board th:nth-child(3),
|
| 609 |
+
.board td:nth-child(3) {
|
| 610 |
+
display: none;
|
| 611 |
+
}
|
| 612 |
+
.board td.num,
|
| 613 |
+
.board th.num {
|
| 614 |
+
width: 100px;
|
| 615 |
}
|
| 616 |
.board .rank {
|
| 617 |
+
width: 44px;
|
| 618 |
}
|
| 619 |
}
|
| 620 |
|