From quantum chemistry to quantum biology: a path toward consciousness
Bibliographic record
Abstract
This paper presents a historical overview of quantum physics methodology's development and application to various science fields beyond physics, especially biology and consciousness. Following a successful interpretation of several early 20th century experiments, quantum physics gradually provided a conceptual framework for molecular bonds via quantum chemistry. In recent years individual biological phenomena such as photosynthesis and bird navigation have been experimentally and theoretically analyzed using quantum methods, building conceptual foundations for quantum physics' entry into biology. Quantum concepts have also been recently employed to explain physiology's allometric scaling laws by introducing quantum metabolism theory. In the second part of this work, we discuss how quantum physics may also be pivotal to our understanding of consciousness, which has been touted by some researchers as the last frontier of modern science. Others believe that consciousness does not belong within the realm of science at all. Several hypotheses, especially the Orch OR theory, have been suggested over the past two decades to introduce a scientific basis to consciousness theory. We discuss the merits and potential extensions of these approaches.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".