# 100. Shell shape and specimen groups

**Question:** How do shell-shape ratios and observed rings differ among recorded specimen categories?

## Result

The largest computed metric is 0.784 for F; the smallest is 0.76 for I. Metric: median_diameter_ratio (Diameter / length).

The source category I denotes infant specimens, not a third adult sex. Ratios use the source scaling consistently.

![Shell shape and specimen groups](outputs/chart.png)

| sex | specimens | median_diameter_ratio | median_height_ratio | median_rings |
| --- | --- | --- | --- | --- |
| F | 1307 | 0.784 | 0.2692 | 10 |
| I | 1342 | 0.76 | 0.25 | 8 |
| M | 1528 | 0.7818 | 0.2679 | 10 |

The chart shows 3 of 3 result rows; the table previews the first 3 in the analysis-defined order. [Download the full result table](outputs/results.csv). Numerical values are computed from the source; missing results stay unavailable.

## Method

Positive-length ratios and category-level robust summaries.

The study uses shared source preparation and reusable statistical routines. Its specific transformations are in [analysis.py](analysis.py), and common model/evaluation code is in [portfolio/methods.py](../../portfolio/methods.py). The [notebook](analysis.ipynb) executes the study and displays the saved results.

## Decision and limitations

Investigate biological sampling composition before pooling specimen categories in a measurement study.

Physical measurements use source scaling. Rings are the modeled target; the source describes an approximate age conversion. Site and animal group identifiers are unavailable, limiting biological generalization. 

Related studies may share observations or holdouts. These are focused analytical studies, not independent replications or deployed business systems. Any model refinements informed by these results need new untouched evaluation data. No commercial impact is inferred from an association or backtest.

## Reproduce

From the repository root, after installing `requirements.txt`:

```powershell
python projects/100-shell-shape-and-specimen-groups/analysis.py
```

Source data are downloaded automatically if absent. Original archives are retained unchanged and checked by SHA-256. The cleaned cache normalizes column names; field-specific changes are visible in [data preparation](../../portfolio/data.py). Runtime evidence is in [receipt.json](outputs/receipt.json).

## Source

[Abalone](https://archive.ics.uci.edu/dataset/1/abalone), Nash et al. (1994). [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Source data are transformed and aggregated in this study. [Source provenance](../../data/provenance/abalone.json) and [prepared-data audit](../../data/provenance/abalone_prepared.json) record the downloaded files, field coverage and hashes.