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Record W1485378455

Awful Splendour: A Fire History of Canada

2007· book· en· W1485378455 on OpenAlexaboutno aff
Stephen J. Pyne

Bibliographic record

VenueMedical Entomology and Zoology · 2007
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyBorealArchaeologyPhysical geographyTaigaForestry
DOInot available

Abstract

fetched live from OpenAlex

Foreword: Mon pays c'est le feu / Graeme Wynn Author's Note: A Boreal Bush Prologue: White Canada Book 1: Torch Kindling Fire Rings of Indigenous Canada Fire and Frost: Tundra Fire and Water: Boreal Forest Fire and Grass, Fire and Leaf: Great Plains Prairies and Great Lakes Forests Fire on the Hills, Fire on the Mountains: Acadian Woods and Cordilleran Forests Fire and Fog: The Incombustible Fringe Tongues of Fire: Black Spruce and High Plains Conflagration and Complex Book 2: Axe Creating Fuel Fire Frontiers of Imperial Canada New Found Land Acadia The Canadas Far Countries With Fire in Their Eyes: Gabriel Sagard and Henry Hind Burning Most Furiously Book 3: Engine Containing Combustion Reconnaissance by Fire: Robert Bell and Bernhard Fernow/ xxx Fire Provinces of Industrial Canada Dominion of Fire: Canada's Quest for Fire Conservancy Sea and Shield: Fire Provinces of Eastern Canada Fire's Lesser Dominion Tracer Index: James G. Wright and Herbert B. Beall Plain and Mountain: Fire Provinces of Western Canada Prosperity and Peril Two Solitudes: C.E. Van Wagner and Donald Stedman Revanchism and Federalism Fire's Outer Limits: Fire Provinces on the Fringe Internal Combustions Epilogue: Green Canada Continental Drift and Global Warming Fire Geography of Green Canada Fire's Reconfederation Settlement Symmetries, Then and Now Counting Carbon Virtual Fire Slow Burns, Fast Flames Fire and Ice Notes Bibliographic Essay Index

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient 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 score0.142
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.006
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.000

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 head0.223
Teacher spread0.213 · 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 teacher head, 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

Citations44
Published2007
Admission routes1
Has abstractyes

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