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Record W4406916805 · doi:10.1038/s41467-024-55789-4

Reply to: On the giant deformation and ferroelectricity of guanidinium nitrate

2025· letter· en· W4406916805 on OpenAlexfundno aff
Durga Prasad Karothu, Rodrigo Cezar de Campos Ferreira, Ghada Dushaq, Ejaz Ahmed, Luca Catalano, Jad Mahmoud Halabi, Zainab Alhaddad, Ibrahim Tahir, Liang Li, Sharmarke Mohamed, Mahmoud Rasras, Pancě Naumov

Bibliographic record

VenueNature Communications · 2025
Typeletter
Languageen
FieldMaterials Science
TopicSolid-state spectroscopy and crystallography
Canadian institutionsnot available
FundersYork UniversityNew York University Abu Dhabi
KeywordsFerroelectricityDeformation (meteorology)NitrateMaterials scienceComputational biologyChemistryBiologyComposite materialOptoelectronicsOrganic chemistry

Abstract

fetched live from OpenAlex

Following a practice of publishing commentaries to articles of other authors ( n.b ., six published comments 1 , 2 , 3 , 4 , 5 , 6 ), Marek Szafrański (MS) and Andrzej Katrusiak (AK) have recently published a Matters Arising article “On the giant deformation and ferroelectricity of guanidinium nitrate” 7 with comments on our article “Exceptionally high work density of a ferroelectric dynamic organic crystal around room temperature” published in Nature Communications 13 , 2823 (2022) 8 . Our detailed analysis of their arguments, provided below, confirms that their claims are biased toward their results, and based on ill-supported data that are not directly comparable to our results. Moreover, they are dismissive of the wealth of electrical, structural, mechanical and computational results presented in our article, contain inconsistencies of their results such as the space groups between their earlier published results and their more recent data, and are altogether scientifically unfounded. Therefore, we reject their comments in their entirety, reiterate our conclusions, and provide further experimental evidence that supports our original results.

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 categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.316
Threshold uncertainty score1.000

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 science0.0020.000
Research integrity0.0010.002
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 head0.018
GPT teacher head0.288
Teacher spread0.271 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2025
Admission routes1
Has abstractyes

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