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Record W3044654283 · doi:10.1002/mma.6714

Morphism classification of a family of transcendent functions arising from pharmacokinetic modelling

2020· article· en· W3044654283 on OpenAlexafffund
Xiaotian Wu, Jun Li

Bibliographic record

VenueMathematical Methods in the Applied Sciences · 2020
Typearticle
Languageen
FieldEngineering
TopicSports Dynamics and Biomechanics
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMathematicsMorphismScope (computer science)Algebraic numberAlgebra over a fieldTranscendental functionFunction (biology)Applied mathematicsNonlinear systemTranscendental numberPure mathematicsCalculus (dental)Mathematical analysisComputer science

Abstract

fetched live from OpenAlex

Many transcendental functions were constructed through finding closed‐form solutions of algebraic or differential equations and become ubiquitous gradually with increasing awareness of applications in specific problems naturally arising from life science. Motivated by Lambert W function, a family of transcendent X functions was introduced recently to express the closed‐form solutions of some nonlinear pharmacokinetic models. Unfortunately, its mathematical properties have not been completely studied. For the purposes of mathematical point of views and the use of wider applications, our objective in this paper is to characterize morphism classification of X functions at the scope of real branches.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.790
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

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

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 head0.153
GPT teacher head0.352
Teacher spread0.199 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations4
Published2020
Admission routes2
Has abstractyes

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