Mwv Episode 72 Jonathan Eisen Evolvability, The Built Environment And Open Science 1280x 720
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Jonathan Eisen is an evolutionary biologist, currently working at University of California, Davis and is the academic editor-in-chief of the open-access journal PLoS Biology. On this episode, Jonathan talks about "evolvability," the probability that organisms can invent new functions. To do this, he has been using genome data in conjunction with experimental information to try and understand the mechanisms by which new functions have originated. Another area of interest for Eisen is the "built environment." We live and work in buildings or structures which are non-natural environments, new to microbes. These "new" environments represent a controlled system in which to study the rules by which microbial communities form. Jonathan is interested in these environments as basic science vehicle and he shares the importance of studying the built environment for science and human health. Finally Jonathan explains his interest in "open science," the ways in which science is shared. At it's core, Eisen wants to leverage cheaper technologies to accelerate the progress of science in a positive way. This episode was recorded at the American Association for the Advancement of Science Meeting in Vancouver, British Columbia on February 18, 2012.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.047 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it