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Multi ∑ QEME of Human Molecular Cell Sustainability in Psycho‐Neuro‐Endo Processes

2019· article· en· W3176012593 on OpenAlexaff
George P Einstein, Michael S Rahman, Orien P Tulp, Carla Koynk

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene Regulatory Network Analysis
Canadian institutionsParkwood Institute
Fundersnot available
KeywordsOrganismPhotobiologyNeuroscienceLiving systemsComputer scienceConceptualizationBiologyCognitive scienceBiochemical engineeringBiological systemEcologyPsychologyArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

The human body dynamics can be modeled as an open system: when in perfect health it is in homeostatic balance physically and emotionally. However, every alteration or disturbance to the foundations of sustainable life such as in the quality of air, water, and nutrients can lead to quantifiable changes in the organism and its cellular environment. These vital biochemical constituents may also be expressed biophysically as Quanta. The master systems of this reactivity, within the biological systems of the body, centrally are directed by the brain/psychological and neurological system, the endocrinological and immunological system. This is also known as the Psycho‐neuro‐‐endocrine‐‐immunological (PNEI) system, which is itself supported by further dynamic co‐physiological systems. The mathematical equation of this triad of congruency is represented: See EQUATION #1 in Figures. Where the above functions or elements are represented as Quanta Energy matrixes. The value of the Quanta Energy of this bio photonic matrix then is a summation of the above matrixes; further evaluations of congruency are made by applying the Planck constant: See EQUATION #2 in Figures. The quantification and understanding of coherence of Quanta influences can provide for future interpretation of these vital biochemical elements and their governing effect on the master control mechanisms and the cellular functions of the organism. Biophysical conceptualization of this also provides the model framework for the incorporation of epigenetic influences as well. Support or Funding Information Support provided by University of Arts, Science, and Technology, Monserrat, BWI This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.040
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.254
Teacher spread0.247 · 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 teacher head, 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

Citations0
Published2019
Admission routes1
Has abstractyes

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