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Record W6902784054 · doi:10.7302/22530

Glaser, Frederick (Fred) interview conducted by Campbell/Spillane

2006· other· en· W6902784054 on OpenAlexaboutno aff

Bibliographic record

VenueDeep Blue (University of Michigan) · 2006
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSubstance abusePublic healthVariety (cybernetics)Service (business)Center (category theory)Field (mathematics)

Abstract

fetched live from OpenAlex

Frederick B. Glaser received his M.D. from Harvard University in 1959 and then served his residency at the U.S. Public Health Service Narcotics Hospital in Lexington, Kentucky. In his interview, he recalls many aspects of his time at Lexington, including the bias against the substance use field at that time, memorable patients, and relations among staff from different disciplines. Glaser went on to have a distinguished career in the field of substance abuse, including the study of opioids and alcohol. In particular, he argued for a range of treatment approaches to address the complex problem of excessive drinking. He has held a variety of positions in the United States and Canada, serving as the director of the University of Michigan Substance Abuse Research Center from 1989 to 1994 before becoming Professor of Psychiatry and Director of the Division on Substance Abuse at the East Carolina University School of Medicine. He is now retired in Greenville, North Carolina. Source: Transcript.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.978
Threshold uncertainty score0.418

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0120.002
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0220.006

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 head0.009
GPT teacher head0.182
Teacher spread0.173 · 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.

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
Published2006
Admission routes1
Has abstractyes

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