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Record W2014451797 · doi:10.1021/je800382b

Heat Capacities of Tetracene and Pentacene

2008· article· en· W2014451797 on OpenAlexaffabout
Michal Fulem, Václav Laštovka, Martin Straka, Květoslav Růžička, John M. Shaw

Bibliographic record

VenueJournal of Chemical & Engineering Data · 2008
Typearticle
Languageen
FieldChemistry
TopicChemical Thermodynamics and Molecular Structure
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTetraceneHeat capacityChemistryPentaceneCalorimeter (particle physics)CalorimetryThermodynamicsMelting pointPhysical chemistryOrganic chemistryDetectorPhysicsMolecule

Abstract

fetched live from OpenAlex

New solid state heat capacity data for tetracene and pentacene are reported in the temperature range (258 to 600) K. The heat capacity measurements were performed using the step method with a Setaram Micro DSC III calorimeter (Institute of Chemical Technology, Prague) and a Setaram TG-DSC 111 (University of Alberta) calorimeter. These new heat capacity data are shown to be in good agreement with one another and with several solid state constant-pressure heat capacity estimation methods and quantum mechanical calculations. The new results highlight errors in the solid state heat capacity and melting point databases for polynuclear aromatic hydrocarbons.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.213
Teacher spread0.197 · 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
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

Citations60
Published2008
Admission routes2
Has abstractyes

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