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same code, new tables #6

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same code, new tables #6

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8 changes: 4 additions & 4 deletions StudentNotebooks/Assignment03/dar-f24-assignment3-template.Rmd
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Expand Up @@ -3,14 +3,14 @@ title: 'CTBench Eval Project Notebook:'
author: "Your Name Here"
date: "`r format(Sys.time(), '%d %B %Y')`"
output:
pdf_document:
toc: true
number_sections: true
fig_caption: false
html_document:
toc: true
number_sections: true
df_print: paged
pdf_document:
toc: true
number_sections: true
fig_caption: false
subtitle: DAR Assignment 3 (Fall 2024)
---
```{r setup, include=FALSE}
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275 changes: 251 additions & 24 deletions StudentNotebooks/Assignment03/dar-f24-assignment3-template.html
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Expand Up @@ -2179,14 +2179,16 @@ <h2><span class="header-section-number">5.1</span> How do results differ
<caption>Differences by Model on CT-Pub</caption>
<colgroup>
<col width="20%" />
<col width="17%" />
<col width="16%" />
<col width="14%" />
<col width="14%" />
<col width="14%" />
<col width="13%" />
<col width="11%" />
<col width="11%" />
<col width="11%" />
</colgroup>
<thead>
<tr class="header">
<th align="left">model</th>
<th align="right">meanPrecision</th>
<th align="right">sePrecision</th>
<th align="right">meanRecall</th>
Expand All @@ -2197,12 +2199,40 @@ <h2><span class="header-section-number">5.1</span> How do results differ
</thead>
<tbody>
<tr class="odd">
<td align="right">0.4344882</td>
<td align="right">0.0084623</td>
<td align="right">0.5272768</td>
<td align="right">0.0104531</td>
<td align="right">0.4517983</td>
<td align="right">0.0072764</td>
<td align="left">gpt4-omni-ts</td>
<td align="right">0.4194773</td>
<td align="right">0.0165780</td>
<td align="right">0.5465613</td>
<td align="right">0.0206740</td>
<td align="right">0.4519953</td>
<td align="right">0.0145372</td>
</tr>
<tr class="even">
<td align="left">gpt4-omni-zs</td>
<td align="right">0.4117923</td>
<td align="right">0.0191232</td>
<td align="right">0.4988831</td>
<td align="right">0.0196749</td>
<td align="right">0.4250843</td>
<td align="right">0.0150289</td>
</tr>
<tr class="odd">
<td align="left">llama3-70b-in-ts</td>
<td align="right">0.4372443</td>
<td align="right">0.0146389</td>
<td align="right">0.5267929</td>
<td align="right">0.0209162</td>
<td align="right">0.4550647</td>
<td align="right">0.0137912</td>
</tr>
<tr class="even">
<td align="left">llama3-70b-in-zs</td>
<td align="right">0.4694388</td>
<td align="right">0.0167251</td>
<td align="right">0.5368701</td>
<td align="right">0.0222861</td>
<td align="right">0.4750490</td>
<td align="right">0.0146080</td>
</tr>
</tbody>
</table>
Expand All @@ -2227,21 +2257,26 @@ <h2><span class="header-section-number">5.2</span> How do results differ
meanRecall=mean(recall),
seRecall=std.error(recall),
meanF1=mean(f1),
sef1=std.error(f1))

kable(CT_Pub_MT_results.df, caption=&quot;Differences by Model and Subgroup on CT-pub&quot;)</code></pre>
sef1=std.error(f1))</code></pre>
<pre><code>## `summarise()` has grouped output by &#39;model&#39;. You can override using the
## `.groups` argument.</code></pre>
<pre class="r"><code>kable(CT_Pub_MT_results.df, caption=&quot;Differences by Model and Subgroup on CT-pub&quot;)</code></pre>
<table>
<caption>Differences by Model and Subgroup on CT-pub</caption>
<colgroup>
<col width="20%" />
<col width="17%" />
<col width="16%" />
<col width="14%" />
<col width="14%" />
<col width="14%" />
<col width="15%" />
<col width="21%" />
<col width="13%" />
<col width="11%" />
<col width="10%" />
<col width="9%" />
<col width="9%" />
<col width="9%" />
</colgroup>
<thead>
<tr class="header">
<th align="left">model</th>
<th align="left">trial_group</th>
<th align="right">meanPrecision</th>
<th align="right">sePrecision</th>
<th align="right">meanRecall</th>
Expand All @@ -2252,12 +2287,204 @@ <h2><span class="header-section-number">5.2</span> How do results differ
</thead>
<tbody>
<tr class="odd">
<td align="right">0.4344882</td>
<td align="right">0.0084623</td>
<td align="right">0.5272768</td>
<td align="right">0.0104531</td>
<td align="right">0.4517983</td>
<td align="right">0.0072764</td>
<td align="left">gpt4-omni-ts</td>
<td align="left">cancer</td>
<td align="right">0.3376333</td>
<td align="right">0.0399497</td>
<td align="right">0.5430899</td>
<td align="right">0.0392855</td>
<td align="right">0.3970881</td>
<td align="right">0.0344699</td>
</tr>
<tr class="even">
<td align="left">gpt4-omni-ts</td>
<td align="left">chronic kidney disease</td>
<td align="right">0.4430021</td>
<td align="right">0.0303595</td>
<td align="right">0.5625353</td>
<td align="right">0.0518243</td>
<td align="right">0.4789217</td>
<td align="right">0.0327797</td>
</tr>
<tr class="odd">
<td align="left">gpt4-omni-ts</td>
<td align="left">diabetes</td>
<td align="right">0.4315031</td>
<td align="right">0.0261183</td>
<td align="right">0.5984520</td>
<td align="right">0.0363788</td>
<td align="right">0.4815179</td>
<td align="right">0.0242987</td>
</tr>
<tr class="even">
<td align="left">gpt4-omni-ts</td>
<td align="left">hypertension</td>
<td align="right">0.4936892</td>
<td align="right">0.0421646</td>
<td align="right">0.5076353</td>
<td align="right">0.0570618</td>
<td align="right">0.4708821</td>
<td align="right">0.0340076</td>
</tr>
<tr class="odd">
<td align="left">gpt4-omni-ts</td>
<td align="left">obesity</td>
<td align="right">0.3882668</td>
<td align="right">0.0495100</td>
<td align="right">0.4659332</td>
<td align="right">0.0487458</td>
<td align="right">0.4034206</td>
<td align="right">0.0390612</td>
</tr>
<tr class="even">
<td align="left">gpt4-omni-zs</td>
<td align="left">cancer</td>
<td align="right">0.3593896</td>
<td align="right">0.0648699</td>
<td align="right">0.5177248</td>
<td align="right">0.0378228</td>
<td align="right">0.3884822</td>
<td align="right">0.0416444</td>
</tr>
<tr class="odd">
<td align="left">gpt4-omni-zs</td>
<td align="left">chronic kidney disease</td>
<td align="right">0.4498255</td>
<td align="right">0.0359125</td>
<td align="right">0.4961775</td>
<td align="right">0.0422165</td>
<td align="right">0.4550535</td>
<td align="right">0.0337143</td>
</tr>
<tr class="even">
<td align="left">gpt4-omni-zs</td>
<td align="left">diabetes</td>
<td align="right">0.4398874</td>
<td align="right">0.0275178</td>
<td align="right">0.5670120</td>
<td align="right">0.0350287</td>
<td align="right">0.4747453</td>
<td align="right">0.0243584</td>
</tr>
<tr class="odd">
<td align="left">gpt4-omni-zs</td>
<td align="left">hypertension</td>
<td align="right">0.4110457</td>
<td align="right">0.0525773</td>
<td align="right">0.4404236</td>
<td align="right">0.0524825</td>
<td align="right">0.3916399</td>
<td align="right">0.0329269</td>
</tr>
<tr class="even">
<td align="left">gpt4-omni-zs</td>
<td align="left">obesity</td>
<td align="right">0.3678517</td>
<td align="right">0.0488932</td>
<td align="right">0.4016209</td>
<td align="right">0.0472745</td>
<td align="right">0.3598584</td>
<td align="right">0.0359429</td>
</tr>
<tr class="odd">
<td align="left">llama3-70b-in-ts</td>
<td align="left">cancer</td>
<td align="right">0.4093769</td>
<td align="right">0.0321481</td>
<td align="right">0.5666599</td>
<td align="right">0.0483330</td>
<td align="right">0.4519619</td>
<td align="right">0.0284682</td>
</tr>
<tr class="even">
<td align="left">llama3-70b-in-ts</td>
<td align="left">chronic kidney disease</td>
<td align="right">0.4538399</td>
<td align="right">0.0367768</td>
<td align="right">0.5158242</td>
<td align="right">0.0568843</td>
<td align="right">0.4591601</td>
<td align="right">0.0350896</td>
</tr>
<tr class="odd">
<td align="left">llama3-70b-in-ts</td>
<td align="left">diabetes</td>
<td align="right">0.4571022</td>
<td align="right">0.0248011</td>
<td align="right">0.5708732</td>
<td align="right">0.0343273</td>
<td align="right">0.4862324</td>
<td align="right">0.0235926</td>
</tr>
<tr class="even">
<td align="left">llama3-70b-in-ts</td>
<td align="left">hypertension</td>
<td align="right">0.4983549</td>
<td align="right">0.0370043</td>
<td align="right">0.4818363</td>
<td align="right">0.0599463</td>
<td align="right">0.4657995</td>
<td align="right">0.0376744</td>
</tr>
<tr class="odd">
<td align="left">llama3-70b-in-ts</td>
<td align="left">obesity</td>
<td align="right">0.3603799</td>
<td align="right">0.0328818</td>
<td align="right">0.4540276</td>
<td align="right">0.0437946</td>
<td align="right">0.3865056</td>
<td align="right">0.0317837</td>
</tr>
<tr class="even">
<td align="left">llama3-70b-in-zs</td>
<td align="left">cancer</td>
<td align="right">0.4138544</td>
<td align="right">0.0414752</td>
<td align="right">0.6322974</td>
<td align="right">0.0492822</td>
<td align="right">0.4836421</td>
<td align="right">0.0366250</td>
</tr>
<tr class="odd">
<td align="left">llama3-70b-in-zs</td>
<td align="left">chronic kidney disease</td>
<td align="right">0.5265988</td>
<td align="right">0.0432749</td>
<td align="right">0.5701615</td>
<td align="right">0.0637368</td>
<td align="right">0.5070008</td>
<td align="right">0.0362418</td>
</tr>
<tr class="even">
<td align="left">llama3-70b-in-zs</td>
<td align="left">diabetes</td>
<td align="right">0.4925006</td>
<td align="right">0.0255036</td>
<td align="right">0.5353139</td>
<td align="right">0.0350723</td>
<td align="right">0.4980289</td>
<td align="right">0.0246477</td>
</tr>
<tr class="odd">
<td align="left">llama3-70b-in-zs</td>
<td align="left">hypertension</td>
<td align="right">0.5075860</td>
<td align="right">0.0488254</td>
<td align="right">0.5109607</td>
<td align="right">0.0630818</td>
<td align="right">0.4757989</td>
<td align="right">0.0373848</td>
</tr>
<tr class="even">
<td align="left">llama3-70b-in-zs</td>
<td align="left">obesity</td>
<td align="right">0.3884561</td>
<td align="right">0.0340609</td>
<td align="right">0.4418456</td>
<td align="right">0.0460536</td>
<td align="right">0.3914692</td>
<td align="right">0.0307577</td>
</tr>
</tbody>
</table>
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