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IN MEMORIAM: JAMES N. M. SMITH, 1944-2005

2007· article· en· W2134902559 on OpenAlexaff
Peter Arcese

Bibliographic record

VenueThe Auk · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsArtPhilosophyEnvironmental ethicsZoologyBiology

Abstract

fetched live from OpenAlex

Fellow from 1994 and recipient of the 2002 Brewster Award, ended an 11-year ba le with cancer on 18 July 2005, at home and with family.Jamie was a gi ed naturalist, unstoppable scientist, consummate teacher and dear friend to many people fortunate enough to have known him well.Jamie's passion and hard work conveyed a positive, encouraging, but critical edge that engaged students and the public alike.He was well known among ornithologists and ecologists for his empirical and synthetic papers in ornithology, ecology, and conservation, but also for his modest nature, constructive advice, provocative questions, and consistently high scientifi c and editorial standards.With collaborators from around the world, Jamie contributed more than 100 papers emphasizing birds, but including work on insects, plants, amphibians, and marine and terrestrial mammals.Jamie also edited or contributed to benchmark books on cooperative breeding, reproductive success, ecosystem dynamics, and cowbirds.In 2006, the work ornithologists most closely associate with Jamie, Conservation and Biology of Small Populations: The Song Sparrows of Mandarte Island, appeared posthumously.It summarizes 28 years of research, for which he was awarded the Brewster Medal.Jamie was a master teacher, training more than 40 students and post-docs directly, and hundreds via commi ee.He was sought out by students with a wide range of interests for his critical mind and legendary editing skills; the la er o en delivered with humor,

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 score0.016
Threshold uncertainty score0.998

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.003

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 head0.246
Teacher spread0.237 · 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
Published2007
Admission routes1
Has abstractyes

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