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Record W2791592069 · doi:10.1016/j.dib.2018.01.102

Data supporting the prediction of the properties of eutectic organic phase change materials

2018· article· en· W2791592069 on OpenAlex
Samer Kahwaji, Mary Anne White

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueData in Brief · 2018
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsEutectic systemEnthalpy of fusionLatent heatMelting temperatureThermodynamicsPhase changeComputer scienceMaterials scienceFusionMicrosoft excelPhase (matter)Melting pointChemistryMetallurgyComposite materialPhysicsOperating systemOrganic chemistryMicrostructure

Abstract

fetched live from OpenAlex

The data presented in this article include the molar masses, melting temperatures, latent heats of fusion and temperature-dependent heat capacities of fifteen fatty acid phase change materials (PCMs). The data are used in conjunction with the thermodynamic models discussed in Kahwaji and White (2018) [1] to develop a computational tool that calculates the eutectic compositions and thermal properties of eutectic mixtures of PCMs. The computational tool is part of this article and consists of a Microsoft Excel® file available in Mendeley Data repository [2]. A description of the computational tool along with the properties of nearly 100 binary mixtures of fatty acid PCMs calculated using this tool are also included in the present article. The Excel® file is designed such that it can be easily modified or expanded by users to calculate the properties of eutectic mixtures of other classes of PCMs.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.264
GPT teacher head0.352
Teacher spread0.087 · 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