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Record W2950679910 · doi:10.1002/ejic.200300471

The Predicted Structures of the New Pnictides HfMQ in Contrast to ZrMQ (M = Ti, V; Q = P, As)

2004· article· en· W2950679910 on OpenAlexaff
Shahab Derakhshan, Enkhtsetseg Dashjav, Holger Kleinke

Bibliographic record

VenueEuropean Journal of Inorganic Chemistry · 2004
Typearticle
Languageen
FieldMaterials Science
TopicIron-based superconductors research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsIsostructuralChemistryChalcogenCrystallographyValence electronElectron countingValence (chemistry)Transition metalMetalAtom (system on chip)Crystal structureTetrahedronElectron

Abstract

fetched live from OpenAlex

Abstract The new pnictides HfTiP, HfTiAs and HfVAs have been prepared through arc‐melting. These arsenides form the predicted structures with (distorted) TiAs4 and VAs4 tetrahedra, while the structures of both Zr analogs (ZrTiAs and ZrVAs) are comprised of TiAs4 and VAs4 square planes, respectively. These differences stem from significant differences in the metal atom substructures. On the other hand, HfTiP and ZrTiP are isostructural. These variations were predicted by utilizing a structure map for metal‐rich pnictides and chalcogenides M2Q (M = valence‐electron poor transition metal, Q = pnicogen or chalcogen) presented in the year 2000. The HfMQ structure is stabilized by strong Hf−Q, M−Q and M−M bonds, and to a minor extent by Hf−Hf and Hf−M bonding interactions. All three new Hf1−δM1+δQ phases exhibit significant phase ranges. (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2004)

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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 designSimulation or modeling
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

Citations7
Published2004
Admission routes1
Has abstractyes

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