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Record W2042181938 · doi:10.1038/npre.2011.6648.1

Benchmarking the SPARC software program for estimating solubilities of naphthalene and anthracene in organic solvents

2011· preprint· en· W2042181938 on OpenAlexaff
Sierra Rayne, Kaya Forest

Bibliographic record

VenueNature Precedings · 2011
Typepreprint
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsSaskatchewan Polytechnic
Fundersnot available
KeywordsAnthraceneNaphthaleneSolubilityChemistryBenchmarkingOrganic chemistryEnvironmental chemistryChemical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract The SPARC software program was benchmarked for calculating the solubilities of two representative polyaromatic hydrocarbons (PAHs), naphthalene and anthracene, in a range of organic solvents at various temperatures. Although SPARC was able to reasonably approximate the solubilities of naphthalene in some organic solvents, gross errors were obtained for other solvents. For anthracene, poor prediction performance was observed in all solvents considered. Overall, the results suggest that SPARC is currently not suitable for accurately predicting the solubilities of representative PAHs relevant for the petroleum sector in various organic solvents.

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)0.003
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.016
GPT teacher head0.280
Teacher spread0.265 · 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
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

Citations1
Published2011
Admission routes1
Has abstractyes

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