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Record W4210318089 · doi:10.53560/ppasa(58-3)602

Analytic Preview of Spectral Contribution of the Neutrinos Emission from Deep Space during Specified Period

2022· article· en· W4210318089 on OpenAlexaboutno aff
Syed Muhammad Ali Abbas Naqvi, Faisal Ahmed Khan Afridi, Bulbul Jan, Muhammad Ayub Khan Yousuf Zai, Mirza Jawad Baig, Arshad Hussain, Syed Muhammad Haroon Rashid, Abid Hussain

Bibliographic record

VenueProceedings of Pakistan Academy of Sciences A Physical and Computational Sciences · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsNeutrinoSolar neutrinoObservatoryExhibitionPhysicsAstrophysicsNeutrino oscillationGeographyParticle physicsArchaeology

Abstract

fetched live from OpenAlex

The earlier period investigations of Neutrinos emission from deep space indicate the existence of this particle which has been detected in various laboratories of the world. These laboratories are responsible for recording neutrinos emission originated from deep space. One laboratory situated near Sudbury, Ontario, Canada known as Sudbury Neutrino Observatory (SNO). Another laboratory is in Japan known as Kamikanado. We obtained a set of observations from both labs. It is obvious that the observations recorded at SNO have been utilized in this manuscript. From the same communication, the neutrino behaviour could be better understood by analyzing the SNO observed data set-I from November 1999 to May 2001 of D2O, while dataset-II is from July 2001 to August 2003 of salt water with particulars recorded, Run start Time since midnight. The samples used in this paper are 250 entries from both the observations sets. In this presentation, the most spectacular exhibition of the neutrino flux in its frequency components of the particles have been depicted in the form of a Periodogram that identifies covariance structure in the neutrino flux reaching this biosphere and parametric values obtained in this paper have been tabulated in various table frame of work. This communication does claim the neutrino emission characteristics in the real world. It has also been known from the literature survey that the same kind of work has not been framed in the third world countries where no neutrino detection laboratories exist. This piece of information will be beneficial for the private and public organizations where the experts are trying to explore deep space emissions detection and their characterization like the present study.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.013
GPT teacher head0.272
Teacher spread0.258 · 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 designSimulation or modeling
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
Published2022
Admission routes1
Has abstractyes

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