MétaCan
Menu
Back to cohort
Record W2107738621 · doi:10.5558/tfc81655-5

Impacts of climate change on diversity in forested ecosystems: Some examples

2005· article· en· W2107738621 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Forestry Chronicle · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsEcosystemEcologyEcosystem diversityClimate changeTundraBiodiversityHabitatRange (aeronautics)GeographyBiology

Abstract

fetched live from OpenAlex

Ecological diversity (the product of ecosystem, species, and genetic diversity) will change significantly in the 21 st Century in response to the combined influence of climate, human activities, the movement of indigenous and non-indigenous species, and natural disturbances like fire (also modified by climate). Many species will acclimate (phenotypic variation) and/or adapt (genotypic variation) to changing conditions. Many will not. Species with a high rate of reproduction that are able to move long distances, rapidly colonize new habitats, tolerate humans, and survive within a broad range of biophysical conditions will be most successful in finding new niches. Large changes in ecosystem composition, structure, and function are expected to occur at northern latitudes and higher altitudes. In some areas novel ecosystems likely will replace existing subalpine, alpine, boreal forest, and tundra ecosystems. Key words: climate change, ecodiversity, forest, ecosystem diversity, species diversity, genetic diversity

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.949

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)0.0000.000

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 head0.053
GPT teacher head0.237
Teacher spread0.184 · 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