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Record W2117473034 · doi:10.12966/jcen.11.02.2013

MRET Water Effect in the TgCRND8 Transgenic Amyloid Mice Models

2013· article· en· W2117473034 on OpenAlexaboutno aff
И. В. Смирнов

Bibliographic record

VenueJournal of clinical and experimental neuroscience · 2013
Typearticle
Languageen
FieldMedicine
TopicBiofield Effects and Biophysics
Canadian institutionsnot available
Fundersnot available
KeywordsGenetically modified mouseTransgeneAmyloid (mycology)ChemistryNeurosciencePharmacologyBiochemistryBiology

Abstract

fetched live from OpenAlex

Th is particular art icle relates to study in vivo regarding the effect of M RET Activated water in Transgenic Amylo id Mice models. It provides some evidence on how MRET Activated water with the mod ified molecu lar structure, physical and electrodynamic characteristics may enhance specific mo lecular mechanisms in living cells. The anomalous proton activity, electrodynamic characteristics and viscosity of MRET Activated water provide some evidence rega rding its possible effect on electrical activity and proper function of the cells. Most cells and tissues have electrical p roperties relevant to their na tural function. The living cells and t issues have rather co mplex structure, consisting of the fold ing memb ranes, the specialized con- nections, and organelles. The localization of electrical properties is particu larly important, since each of the co mplex stru ctures must be expected to have a specific ro le in the electrical function of the tissue. MRET Activ ated water with modified proton activity and electrical conductivity can also have ability to enhance a proton pump activity of the cells. As a result it may lead to the restoration of the transduction signaling and the restoration of normal cellu lar funct ions. The clinical study in vivo in Transgenic Amyloid M ice models conducted at Toronto University proves the validity of the proposed hypothesis.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.051
GPT teacher head0.365
Teacher spread0.314 · 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 designBench or experimental
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

Citations2
Published2013
Admission routes1
Has abstractyes

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