The sounds of science—a symphony for many instruments and voices
Bibliographic record
Abstract
Sounds of Science is the first movement of a symphony for many (scientific) instruments and voices, united in celebration of the frontiers of science and intended for a general audience.John Goodenough, the maestro who transformed energy usage and technology through the invention of the lithium-ion battery, opens the programme, reflecting on the ultimate limits of battery technology.This applied theme continues through the subsequent pieces on energy-related topics-the sodium-ion battery and artificial fuels, by Martin Månsson-and the ultimate challenge for 3D printing, the eventual production of life, by Anthony Atala.A passage by Gerianne Alexander follows, contemplating a related issue: How might an artificially produced human being behave?Next comes a consideration of consciousness and free will by Roland Allen and Suzy Lidström.Further voices and new instruments enter as Warwick Bowen, Nicolas Mauranyapin and Lars Madsen discuss whether dynamical processes of single molecules might be observed in their native state.The exploitation of chaos in science and technology, applications of Bose-Einstein condensates and the significance of entropy follow in pieces by Linda Reichl, Ernst Rasel and Roland Allen, respectively.Mikhail Katsnelson and Eugene Koonin then discuss the potential generalisation of thermodynamic concepts in the context of biological evolution.Entering with the music of the cosmos, Philip Yasskin discusses whether we might be able to observe torsion in the geometry of the Universe.The crescendo comes with the crisis of singularities, their nature and whether they can be resolved through quantum effects, in the composition of Alan Coley.The climax is Mario Krenn, Art Melvin and Anton Zeilinger's consideration of how computer code can be autonomously surprising and creative.In a harmonious counterpoint, his 'Guidelines for considering AIs as coauthors', Roman Yampolskiy concludes that code is not yet able to take responsibility for coauthoring a paper.An interlude summarises a speech by Zdeněk Papoušek.In a subsequent movement, new themes emerge as we seek to comprehend how far we have travelled along the path to understanding, and speculate on where new physics might arise.Who would have imagined, 100 years ago, a global society permeated by smartphones and scientific instruments so sophisticated that genes can be modified and gravitational waves detected?
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.028 | 0.011 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".