DT: “For validating, or Proving that the visual standards are reliable, here's my plan.”
You didn’t finish the plan—so let me sketch a clean validation approach, and you can tell me how it matches what you had in mind.
1. Lab-style accuracy test
Goal: Does the visual method correctly estimate known application rates?
Create test panels
Prepare, say, 20–30 1‑sq‑ft panels.
For each panel, secretly apply a known amount of salt (e.g., 3, 4, 5, 6, 7 lb/1000 sq ft equivalents), but don’t tell the raters.
Have raters use your visual standards
Give them only your photo card.
Ask them to estimate the rate for each panel by choosing the closest standard (or “between X and Y”).
Compare estimates to truth
Calculate how often they’re:
exactly right
within ±1 level
clearly off
If most estimates land within one level of the true rate, that’s strong evidence your standards are reliable.
2. Field realism test
Goal: Does it still work under real conditions?
Have a truck spread salt on a test area at different controller settings.
Randomly select 1‑sq‑ft spots, photograph them, and have raters estimate the rate using your standards.
Independently measure those same spots:
Sweep and collect salt from the 1‑sq‑ft area.
Weigh it.
Convert to lb/1000 sq ft.
Again, compare visual estimates to measured values.
3. Operator consistency test
Goal: Do different people see the same thing?
Use the same set of test images or panels.
Have multiple operators/inspectors independently estimate the rate.
Look at:
agreement between people (do they pick the same level?)
bias (do some always over‑estimate?)
If people are consistent with each other and close to the true values, your tool is both reliable and usable.
You’re on a terrific track here — what you’ve outlined is exactly the kind of validation study that would convince a city, DOT, or academic reviewer that your visual standards are reliable, repeatable, and meaningful. And yes, you can absolutely build a simple program to run the test and then output a clean dataset for analysis.
Before I write any code, let me shape your plan into a tight, workable design so the program does exactly what you need.
Your Validation Plan (Refined and Strengthened)
1. You create the “unknown” test images
Each image shows a 1‑sq‑ft patch of pavement with a known salt weight.
You keep the true weights hidden from observers.
2. Observers complete a rating task
Each observer sees:
One “unknown” image at a time.
A scrollable sequence of your standard reference images (least → most salt).
For each unknown image, they record:
Best match (the standard image number)
Second‑best match (the next closest)
Each observer does ~10 trials.
3. The program saves all responses
For each trial, it stores:
Observer ID
Trial number
Unknown image ID
True salt weight (hidden from observer but stored in data)
Best match
Second best match
Time taken (optional but useful)
4. After all observers finish, the program outputs:
A CSV or spreadsheet‑style table of all raw responses
Summary statistics:
% correct (best match = true level)
% within ±1 level
Confusion matrix (which levels get confused with which)
Inter‑rater agreement (Cohen’s κ or Fleiss’ κ)
Bias analysis (do people systematically over‑ or under‑estimate?)
This is exactly the kind of analysis that demonstrates reliability.
Now — the program you’re asking for
You want:
A simple interface
Observers scroll through standards
They click a key for “best match” and another for “second best”
Data saved automatically
A script to analyze the results
I can absolutely write this for you.
But I need one key detail before I generate the code:
Which environment do you want the program in?
Option A — Python (recommended)
Runs on any computer
Easy to distribute
Can include both the rating interface and the statistics
Uses libraries like:
tkinterfor the interfacepandasfor datascikit-learnfor agreement statistics
Option B — Web-based (HTML/JavaScript)
Runs in any browser
Easiest for observers
Saves data to a file or server
No installation needed
Option C — PowerPoint + Excel hybrid
Surprisingly workable
Observers click through slides
Data collected manually
No coding required
But less elegant and harder to automate
Option D — R / Shiny app
Very clean statistical workflow
Web-like interface
Great for academic publication
Requires R installed
Tell me which environment you prefer
Once you choose, I’ll generate:
The full program
Instructions for how to run it
The data format
The statistical analysis script
A clean output table you can hand to reviewers or city staff
Just tell me A, B, C, or D, and I’ll build the whole thing.
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How would I receive the code, and how would I put it into my lenovo yoga pro 9i? Briefly, so I can have confidence to proceed, since I am not a computer nerd.
You don’t need to be a “computer person” to run this kind of program on your Lenovo Yoga Pro 9i. Let me give you the simplest, confidence‑building explanation of how you would receive the code and how you would run it, without any technical overwhelm.
⭐ How you would receive the program
I can give you the program in one of two easy formats:
Option A — A single text file containing the code
You copy‑and‑paste it into a program on your computer (I’ll tell you exactly which one).
Option B — A ZIP folder containing everything ready to run
You download it, double‑click it, and run the program by clicking an icon.
Either way, you don’t need to “install” anything complicated.
⭐ How you would run it on your Lenovo Yoga Pro 9i
Your Yoga Pro 9i runs Windows, so here’s the simplest path:
1. Install Python (free, safe, one‑time)
This is just like installing any normal app.
- Go to the official Python website
- Click “Download Python”
- Double‑click the installer
- Check the box that says “Add Python to PATH”
- Click Install
That’s it. One time only.
(If you prefer, I can walk you through this step‑by‑step.)
2. Put the program folder anywhere you like
For example:
- Desktop
- Documents
- Downloads
Inside the folder you’ll have:
- The program file (e.g.,
salt_visual_test.py) - A folder of your standard images
- A folder of your unknown test images
I’ll structure it for you.
3. Double‑click the program to run it
If we build it as a simple graphical program (which I recommend), you’ll just:
- Double‑click the file
- A window opens
- Observers scroll through the standards
- They click “Best match” and “Second best”
- The program saves their answers automatically
No command lines, no typing, no technical steps.
4. After observers finish, you open the results file
The program will automatically create a file like:
results.csv
You can open this in:
- Excel
- Google Sheets
- Anything you like
It will contain:
- Observer ID
- Trial number
- Unknown image ID
- True salt weight
- Best match
- Second best match
- Time taken
5. I can also give you a second program that analyzes the results
You double‑click it, and it prints:
- Accuracy
- “Within one level” accuracy
- Confusion matrix
- Inter‑rater agreement
- Bias (over‑ or under‑estimation)
Again, no technical steps required.
Bottom line
You will NOT be writing code.
You will NOT be using a terminal.
You will NOT be debugging anything.
You will simply:
- Install Python once
- Download a folder I prepare
- Double‑click the program
- Collect results
- Double‑click the analysis program
That’s it.
If you want, I can now:
- Build the exact program you described
- Make it as simple as double‑clicking an icon
- Include clear instructions written for non‑technical users
Just tell me:
Do you want the program in Python with a simple graphical window (the easiest option)?
DT: You said that someone might pick a second best far in steps from the best. I can't imagine they would do that. It would be a sign they weren't paying attention, or didn't understand the task
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