MétaCan
Menu
Back to cohort
Record W2592364053 · doi:10.1080/03632415.2017.1293964

T<scp>homas</scp> P<scp>aul</scp> S<scp>imon</scp>

2017· article· en· W2592364053 on OpenAlexaboutno aff
Douglas D. Kane

Bibliographic record

VenueFisheries · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWifeFish <Actinopterygii>SociologyArt historyHistoryLawBiologyFisheryPolitical science

Abstract

fetched live from OpenAlex

On July 16, 2016 Thomas Paul Simon, Ph.D. of Bloomington, Indiana passed away unexpectedly. Dr. Simon was a well‐known aquatic ecologist and ichthyologist with degrees from three Big Ten institutions and teaching experience at three additional Big Ten schools. Tom, as he was known by his friends and colleagues, is survived by his wife of 35 years, Marybeth Simon; sons, Thomas Paul Simon, IV, Cameron Simon, and Zachary Simon, and daughter, Lia Simon, all of Bloomington; mother, Marcella Simon of Harrison Township, MI; sisters, Lisa Farnsworth of Clinton Township, MI, and Carla Price (Edward) of McComb, MI. His father preceded him in death. Simon was born in Mt. Clemens, Michigan on February 22, 1959. He attended the University of Michigan and was an honorable mention for All‐American honors (1980) in men's lacrosse at attack, their leading goal scorer (1979, 1980), Rookie of the Year (1978), and part of the Big Ten All Star Team (1981). Lacrosse would continue to play an important part of his life, as a semi‐professional player in Canada, member of the U.S. team, and coach for girl's lacrosse.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.276
Threshold uncertainty score0.393

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.7240.431

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 head0.015
GPT teacher head0.220
Teacher spread0.205 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueFisheriesSame topicFish Ecology and Management StudiesFrench-language works237,207