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Record W3002304960 · doi:10.1021/cen-09803-scicon1

7 molecular scientists killed in Iran plane crash

2020· article· en· W3002304960 on OpenAlexaboutno aff
Sam Lemonick

Bibliographic record

VenueC&EN Global Enterprise · 2020
Typearticle
Languageen
FieldMedicine
TopicBiotechnology and Related Fields
Canadian institutionsnot available
Fundersnot available
KeywordsWifeCrashProduct (mathematics)EngineeringAeronauticsQuality (philosophy)On boardManagementPsychologyMedical educationPolitical scienceLawMedicinePhysicsMathematicsComputer science

Abstract

fetched live from OpenAlex

A chemist working at a product-testing company and six graduate students in molecular science fields died earlier this month when Ukraine International Airlines Flight 752 was shot down over Tehran, Iran. The plane was flying from Tehran to Kiev, Ukraine, and the seven chemists were traveling separately to Canada. All 176 passengers on board died in the accident. Fareed Arasteh, 32, was a first-year PhD candidate at Carleton University. He was working to identify and characterize new gene factors involved in the quality-control processes that fungal cells use to ensure the right genes get expressed. Arasteh had returned to his home in Iran between semesters to get married. His wife was not aboard the flight. His adviser, Ashkan Golshani, says Arasteh was a humble, approachable person who always had a smile on his face and was very dedicated to science. Arasteh, Golshani says, was excited about asking questions no one

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.802

Codex and Gemma teacher scores by category

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 integrity0.0010.001
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 head0.007
GPT teacher head0.253
Teacher spread0.246 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2020
Admission routes1
Has abstractyes

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