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Record W4386289068 · doi:10.1088/978-0-7503-5321-2ch10

The chemical master equation

2023· book-chapter· en· W4386289068 on OpenAlexaff
Marc R. Roussel

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldChemistry
TopicVarious Chemistry Research Topics
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsMathematics

Abstract

fetched live from OpenAlex

The stochastic theory that will be presented in this chapter applies equally well to gas-phase reactions as to solution-phase reactions. It is developed here because it follows naturally from our treatment of master equations in the previous chapter. But this theory will be particularly useful in biochemistry, where some key molecules are present in extremely small numbers in a solution environment. For example, think about a human gene present in a cell in two copies. Suppose that when a repressor protein is bound to the gene, transcription can’t be initiated. We surely can’t treat the number of active (unbound) copies of the gene as a continuous variable, since it can only take the values zero, one, or two, depending on whether both copies are bound by the repressor, one copy is bound, or neither, respectively. This is an extreme, of course, but both biochemistry and nanotechnology often involve systems with just a few dozen molecules of a particular type.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.677
Threshold uncertainty score0.998

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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.092
GPT teacher head0.277
Teacher spread0.185 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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