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Record W4221039239 · doi:10.25011/cim.v45i1.38099

Young Investigator Interview With CSCI Distinguished Scientist Awardee Dr. Michael Hill

2022· article· en· W4221039239 on OpenAlexafffundvenueabout
Wenxuan Wang, Michael D. Hill

Bibliographic record

VenueClinical and investigative medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsFoothills Medical CentreUniversity of CalgaryWestern University
FundersUniversity of Calgary
KeywordsMedicineGerontologyLibrary scienceManagementPsychologyComputer science

Abstract

fetched live from OpenAlex

Dr. Michael Hill is President of the Canadian Neurology Federation and Director of the Stroke Unit for the Calgary Stroke Program. He is also a professor at the University of Calgary at the Department of Clinical Neurosciences. Dr. Hill has made outstanding contributions to the field of stroke research, particularly through the ESCAPE and ESCAPE-NA1 trials. Dr. Hill was a recipient of the Canadian Society for Clinical Investigation (CSCI) Distinguished Scientist Award in 2021-recognized as an expert and innovative leader in his research.

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)0.018
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0130.003
Scholarly communication0.0070.004
Open science0.0030.005
Research integrity0.0140.028
Insufficient payload (model declined to judge)0.0140.007

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 head0.132
GPT teacher head0.343
Teacher spread0.210 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes4
Has abstractyes

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