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Record W7066114600

Florida Panthers Name Richard Pollock, 08, Pro Scout

2016· article· en· W7066114600 on OpenAlexaboutno aff

Bibliographic record

VenueUND Scholarly Commons (University of North Dakota) · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodHyporeflexiaTSG101Articular cartilage damageDemotion
DOInot available

Abstract

fetched live from OpenAlex

The Florida Panthers announced today the hiring of Richard Pollock as a professional scout and Josh Weissbock as a prospect consultant. A native of Winnipeg, Manitoba, Pollock founded the hockey news and analysis website IllegalCurve.com in 2007, one of the first of its kind. His writing has also been featured on ESPN and Hockey Prospectus. Most recently, Pollock has served as the lead analyst on the weekly “IllegalCurve Hockey Show” on Winnipeg’s TSN affiliate, AM 1290, and as a color commentator and analyst during select NHL broadcasts on the same station. Pollock, a lawyer in Winnipeg, is a 2008 graduate of the University of North Dakota School of Law. Since 2011, Weissbock, a native of Vancouver, British Columbia, has been involved in hockey research and writing in the area of prospect analysis. He has consulted for various professional, amateur, and national teams and presented at industry conferences. Weissbock studied Computer Science, Machine Learning and Natural Language Processing at the University of Ottawa, where he earned his master’s in 2014 and was an Academic All-Canadian (Rowing). Weissbock will continue his current professional role working for the Canadian government.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0000.000
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 head0.016
GPT teacher head0.222
Teacher spread0.206 · 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; both teacher heads agree on what is shown here.

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
Published2016
Admission routes1
Has abstractyes

Explore more

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