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Record W7139249844

Ralph Keef

2012· article· W7139249844 on OpenAlexaboutno aff
University of Maine Pulp & Paper Foundation

Bibliographic record

VenueDigitalCommons (California Polytechnic State University) · 2012
Typearticle
Language
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsMillNova scotiaCertificateChief executive officerVice presidentPulp millWest virginia
DOInot available

Abstract

fetched live from OpenAlex

Ralph C. Keef was born in St. Stephens, New Brunswick, Canada, in December 1933. He grew up in Vanceboro, Maine. His father and grandfather owned land and woods operations in Washington County and in Charlotte County, New Brunswick. Keef attended the University of Maine where he received a B.S. in Chemical Engineering, a Certificate in Pulp and Paper Management, and in 1958, an M.S. in Pulp and Paper Technology. Keef’s professional career began in Ketchikan and Sitka, Alaska with the Alaska Lumber and Pulp Company. In 1961, Keef joined the St. Croix Paper Company in Woodland, Maine and then, as a result of a merger was employed by Georgia Pacific. In 1967, Keef joined Great Northern Paper in Millinocket. In 1973, Keef became the Resident Manager and Chairman of the Executive Committee of Nova Scotia Forest Industries in Port Hawkesbury, a mill complex owned by the Swedish-owned company Stora Kopparberg. He later transferred to their paper mill in New Falls, New York as Vice President where he stayed until retiring in 1987. Keef recipient served as a member of the University of Maine’s Pulp & Paper Foundation Investment Management Committee becoming its Chair in 2001. Keef died on July 9, 2015, at his home in Hermon, Maine following a series of strokes.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.007
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.015

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 head0.012
GPT teacher head0.189
Teacher spread0.177 · 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 designNot applicable
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
Published2012
Admission routes1
Has abstractyes

Explore more

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