131 to 140 of 138,093 Results
May 20, 2026 -
A dataset of AI-generated podcasts created using NotebookLM
Plain Text - 5.3 KB -
MD5: 77b403040b76cefce93200d757fed2d4
Transcript of podcast with same filename ending in .wav. |
May 20, 2026 -
A dataset of AI-generated podcasts created using NotebookLM
Waveform Audio - 11.1 MB -
MD5: 6b6521a8d9246c4c33c217c94c1268a0
Audio of a podcast generated on 23 September 2024 by NotebookLM in response to an uploaded PDF with no content. |
May 20, 2026 -
A dataset of AI-generated podcasts created using NotebookLM
Plain Text - 1.4 KB -
MD5: 9647bcbc60a19c567ef8240ce9665562
Plain text file containing the text of the joke that was pasted into NotebookLM's sources, and provenance information about the joke, which has been circulated in print since at least 1994 and online since at least 2006. |
May 20, 2026 -
A dataset of AI-generated podcasts created using NotebookLM
Adobe PDF - 12.4 MB -
MD5: 3bcb95e7af1fcfa8b50b8dbd3e75f0eb
Papers for the 10 September 2024 meeting of the Faculty Board of the Humanities Faculty at the University of Bergen in Norway. The papers are public documents, and are available at https://ekstern.filer.uib.no/hf/Fakultetsstyre/Styresaker%202024/10.09.2024/Offentlig%20m%C3%B8teinnkalling%2010.09.2024.PDF or on request by emailing post@uib.no. |
May 20, 2026 -
A dataset of AI-generated podcasts created using NotebookLM
Adobe PDF - 3.7 KB -
MD5: c934d95b02b4ee0c4e367d9cb8188ab8
The empty PDF file that was uploaded to NotebookLM to generate podcasts. The file was created from a plain text document with no text other than a single space that was printed to PDF on a Mac in 2024. |
May 20, 2026 -
A dataset of AI-generated podcasts created using NotebookLM
Plain Text - 4.1 KB -
MD5: fc4e2336efcbe75ea9b2875c8c6f4c4d
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Adobe PDF - 3.1 MB -
MD5: 01331e81efc1de68d50703903d7ca590
Supplementary figure S1: Curve fitting with different degrees of smoothing. The plots (A-C) shows the 0-120 min postprandial data from 10 randomly selected participants, together with their respective smoothed postprandial curve. Each subplot shows smoothing with a specific value of teh smoothing parameter, lambda, as indicated in the plot title. T... |
Adobe PDF - 10.5 MB -
MD5: 7967fc349f6e7d17c8e6c462ff6668f0
Supplementary figure. S2: Plots of all smooth postprandial curves.
The 16 separate plots show the estimated postprandial curves based on fasting and postprandial measurements of, respectively, alanine aminotransferase, albumin, alkaline phosphatase, bilirubin, C-reactive protein, free thyroxine, glucose, gamma-glutamyl transferase, High-density... |
Adobe PDF - 18.0 MB -
MD5: 00476f82bc8b73f7e76ed317fd286af3
Supplementary Fig. S3: FPCA of all postprandial variables.
The 32 sets of plots (one set of plots at each page) show the results from functional principal component analyses (FPCA) of the postprandial curves of the 15 postprandial variables, and incremental triacylglycerol.
Both the FPCA of the 0-120 minute interval and the 0-240 interval is pre... |
Adobe PDF - 115.0 KB -
MD5: 8c26e4642e0f55aea074883567935de4
Supplementary Fig. S4: Plots of FPC curves, harmonics.
The plots show the three first functional principal component curves (FPCs, harmonics) for glucose, C-peptide, TAGs, and incremental TAGs, respectively.
In all plots, the black, solid line represents the first FPC, the red dashed line represents the second FPC, and the green dotted line repr... |
