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Quantitative Convergence between Physical-Chemical Constants of the Proton and the Properties of Water: Implications for Sequestered Magnetic Fields and a Universal Quantity

2013· article· en· W1491714446 on OpenAlexaff
Michael A. Persinger

Bibliographic record

VenueInternational Letters of Chemistry Physics and Astronomy · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMagnetic and Electromagnetic Effects
Canadian institutionsLaurentian University
Fundersnot available
KeywordsProtonMagnetic fieldMagnetic momentPhysicsChemical physicsAtom (system on chip)ChemistryAtomic physicsMolecular physicsCondensed matter physicsQuantum mechanics

Abstract

fetched live from OpenAlex

The ratio of the magnetic moment and charge of a proton when multiplied by the viscosity of water results in forces that when applied over the distance of O-H bonds provides quantum increments in the order of 10-20 J. Precise coefficients of this order of magnitude are consistent with the mechanisms associated with proton (H+) mobility and duration of the hydronium atom. When applied to aggregate properties of water that involve exclusion zones defined by boundaries containing marked proton density and coherent domains within which specific patterns of applied magnetic fields can be contained for protracted periods, these intrinsic properties suggest that the major features of the cell plasma membrane and living systems can be accommodated by proton movements within water. Water exposed in the dark to weak magnetic fields displayed a ~10 nm shift in peak wavelength as measured by a fluorescence spectrophotometer. Given the persistent emergence of 10-20 J as a functional unit of energy across the universe, the physical significance of the interaction between weak, temporally patterned magnetic fields and the organization of water within astronomical and abiogenic contexts may have been underestimated.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.004
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.009
GPT teacher head0.221
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2013
Admission routes1
Has abstractyes

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