WEBVTT

1
00:00:00.322 --> 00:00:02.712
A coding agent can write an experiment.

2
00:00:02.712 --> 00:00:06.508
Allagma gives it a research workflow that leaves a checkable
record.

3
00:00:06.508 --> 00:00:10.338
Start with a small question: does adding a bias increase squared
error?

4
00:00:12.423 --> 00:00:15.838
This button runs the actual offline example on this machine.

5
00:00:15.838 --> 00:00:20.966
Two pilot controls qualify the runner, followed by twenty-four
new confirmation seeds.

6
00:00:20.966 --> 00:00:23.540
A failure and an interruption are deliberate.

7
00:00:23.540 --> 00:00:27.656
Their retries get new identities, and every attempt stays in the
record.

8
00:00:32.470 --> 00:00:36.608
The generated figure shows individual paired differences, not
just the average.

9
00:00:36.608 --> 00:00:42.670
Adding the bias raises mean squared error here, but three seeds
favor the biased estimator and one is tied.

10
00:00:42.670 --> 00:00:45.821
The interval is an explicitly approximate calculation.

11
00:00:46.553 --> 00:00:48.708
The claim ledger keeps that distinction.

12
00:00:48.708 --> 00:00:50.749
Higher average error is supported.

13
00:00:50.749 --> 00:00:53.408
Higher error on every seed is contradicted.

14
00:00:53.408 --> 00:00:58.483
Each statement points to the exact numerical evidence, with its
scope and limitations.

15
00:01:01.637 --> 00:01:07.044
The study writes a report with methods, measured results,
limitations, and an evidence chain.

16
00:01:07.044 --> 00:01:12.035
These are ordinary files you can read, share, and inspect
without a hosted dashboard.

17
00:01:13.696 --> 00:01:19.152
Run the audit to recompute the analysis and manuscript, and
verify five hundred twenty-one evidence references.

18
00:01:19.152 --> 00:01:23.048
This is deterministic verification, not independent scientific
peer review.

19
00:01:23.766 --> 00:01:27.840
For your own question, a native agent develops the study-owned
science.

20
00:01:27.840 --> 00:01:33.152
These are retained results from a real weight-averaging study,
not new training in this recording.

21
00:01:33.152 --> 00:01:35.064
Start with the offline tutorial.

22
00:01:35.064 --> 00:01:36.664
Then follow the evidence.