MétaCan
Menu
Back to cohort
Record W2763881669 · doi:10.5539/mas.v11n11p9

Testing of Locally Available Jordanian Materials for Hydrogen Storage

2017· article· en· W2763881669 on OpenAlexvenueno aff
Yousef Abdallat, Jehad Yamin

Bibliographic record

VenueModern Applied Science · 2017
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsnot available
Fundersnot available
KeywordsHydrogen storageMagnesiumNickelMaterials scienceHydrogenChemical engineeringMetallurgyChemistryOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Several locally available materials were tested for hydrogen storage. This study was conducted theoretically using suitable software. The materials tested were Sweileh |San, Zeolite, Nickel, Magnesium and Lanthanium. It was found that using the locally available Sweileh sand alone did not give promising results. Pure Magnesium showed the best results followed with Nickle then lanthanium. On mixture basis, adding Magnesium to local Sweileh sand improved its storage ability more than adding other materials like Ni or La.

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 score0.003
Threshold uncertainty score0.010

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.041
GPT teacher head0.271
Teacher spread0.230 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueModern Applied ScienceSame topicHydrogen Storage and MaterialsFrench-language works237,207