MétaCan
Menu
Back to cohort
Record W4385870777 · doi:10.59962/9780774856294-001

Foreword

2000· book-chapter· en· W4385870777 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2000
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

In the 86 years since The Natural History of the Toronto Region, the precursor to the present book, was published, the city and indeed the world have changed almost beyond recognition.What remains recognizable are the 'special places,' the ecosystems of Toronto and the earth.As a scientist, and as an astronaut who has seen the planet from the unique viewpoint of the space shuttle Discovery, I know both how glorious and how fragile those ecosystems are.The wonders of the everyday world we citizens of Toronto enjoy, often without realizing the complexity of our natural environment, are celebrated in Special Places.But this book is more than a guide; it is a series of thoughtful and carefully researched essays by Dr. Betty I. Roots and her co-editors, Drs.Donald A. Chant and Conrad E. Heidenreich, and many contributors.They offer us a fascinating spectrum -from the vast perspectives of palaeontology, to the portraits of First Peoples, to close-ups of mosses and lichens.Together, these scholars and educators have produced a wonderful present for the Royal Canadian Institute, Canada's oldest active scientific society, 150 years old in 1999-Torontonians and all the readers of Special Places owe the Royal Canadian Institute a debt of gratitude for showing us all how the city has changed and what we must do to care for the special place on the planet that Toronto inhabits.The past has been recalled; the present is described lovingly; and the future is ours to create.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.340
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0060.004
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.6600.633

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 head0.172
Teacher spread0.159 · 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
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of British Columbia Press eBooksSame topicPolar Research and EcologyFrench-language works237,207