A physical mechanism of magnetoreception: Extension and analysis
Bibliographic record
Abstract
Proposed is a general physical mechanism of magnetoreception of weak magnetic fields (MFs). The mechanism is based on classical precessional dynamics of a magnetic moment in a thermally disturbed environment and includes a minimum of necessary parameters-the gyromagnetic ratio, thermal relaxation time, and rate of downstream events generated by changes in the state of the magnetic moment. The mechanism imposes general restrictions on the probability of initial biophysical magnetic transduction event before the involvement of specific biophysical and biochemical mechanisms-i.e., regardless of the nature of an MF target and the subsequent cascade of events. It is shown that biological effects of weak MFs have, in certain cases, nonlinear and frequency selective properties. The observation of these characteristics provides information not only on the target's gyromagnetic ratio, but also on the parameters of its interaction with the immediate environment. This enables one to develop experimental strategies for identifying the biophysical mechanisms of magnetoreception including the specific case of effects of a near-zero MF exposure. The mechanism is universally applicable to magnetic moments of different nature, in particular, of electron and proton orbital motion and of spins. Experimental exposure conditions are derived which would lead to validation of the proposed mechanism. Bioelectromagnetics. 38:41-52, 2017. © 2016 Wiley Periodicals, Inc.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".