MétaCan
Menu
Back to cohort
Record W2933298028 · doi:10.1139/cjp-2019-0015

Revisiting the tellurium clusters (Te<sub><i>n</i></sub>; <i>n</i> = 2–8) using ab initio methods

2019· article· en· W2933298028 on OpenAlexvenueno aff
Hassan H. Abdallah

Bibliographic record

VenueCanadian Journal of Physics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsAb initioCluster (spacecraft)Bond lengthTelluriumAtomic physicsAb initio quantum chemistry methodsStability (learning theory)Molecular orbitalMolecular physicsMolecular geometrySpectral lineMoleculeChemistryQuantum mechanics

Abstract

fetched live from OpenAlex

The optimized geometries and vibrational frequencies of Te clusters n = 2–8 are calculated using ab initio molecular orbital theory at B3LYP, MP2, BLYP, and BH–HLYP levels of approximation. We found that Te8 (D4d) cluster has the highest stability followed by Te7 and Te6 (D3d). The computed vibrational frequencies have small systematic deviations with IR spectra for crystalline Te5, Te6 (C2v). The stability of positively and negatively charged Te clusters is determined by the B3LYP method. This is because the B3LYP method demonstrated the best stability in every cluster geometry. In general, the results showed that the negatively charged clusters have the highest stability, followed by neutral clusters, and finally positively charged clusters. However, the predicted bond angle and bond distance for every cluster geometry displayed very close values with different levels of calculations. These calculations will provide predictions for future experimental studies.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.275
Teacher spread0.255 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of PhysicsSame topicAdvanced Chemical Physics StudiesFrench-language works237,207