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Record W2591654388 · doi:10.1021/cen-09506-notw13

Chemist among Quebec shooting victims

2017· article· en· W2591654388 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueC&EN Global Enterprise · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicForensic Fingerprint Detection Methods
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryChemistAgricultureEngineeringWork (physics)Political scienceManagementChemistrySociologyLibrary scienceLawHistoryOrganic chemistryMechanical engineeringArchaeologyEconomics

Abstract

fetched live from OpenAlex

A chemistry professor was among six people killed during a shooting on Sunday at a Quebec City mosque. Khaled Belkacemi, 60, was a professor in the Faculty of Agriculture & Food Sciences at Laval University. “He was a cultured and passionate man and very involved within the faculty,” says Jean-Claude Dufour, dean of the Faculty of Agriculture & Food Sciences at Laval University. “His remarkable contributions will endure despite his sudden passing, which deeply saddens us all.” Belkacemi’s research focused on the use of heterogeneous catalysis in food chemistry and in the conversion of biomass and food waste. He earned an M.S. in chemical engineering from the University of Sherbrooke in 1986 and later earned a Ph.D. from the same university in 1990. He also earned a Ph.D. in chemical engineering from the Algerian Ministry of Higher Education in 1995. “He firmly believed that his work in food engineering should

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.357
Teacher spread0.343 · 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