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Record W2277430993 · doi:10.7202/1000415ar

Contemporary pollen spectra in the James Bay Lowland, Canada, and comparison with other forest-tundra assemblages

2011· article· en· W2277430993 on OpenAlexaffvenueabout
L. D. Farley-Gill

Bibliographic record

VenueGéographie physique et Quaternaire · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsPollenTundraTaxonShrubMossBayCallunaEcologyBotanyGeographyBiologyEricaceaeArchaeologyArctic

Abstract

fetched live from OpenAlex

Contemporary pollen spectra obtained from twenty-eight sites in the southwestern James Bay area were examined as an aid to the interpretation of postglacial pollen diagrams. Picea is the dominant pollen type. Pinus banksiana and Betula pollen are prominent, with the shrub birches contributing most of the latter. Other tree genera (Larix, Abies, Populus) extant in the area are underrepresented in the pollen assemblages. Among the shrub taxa present, pollen of two species of Alnus, A. crispa and A. rugosa, are regionally represented. Salix and Myrica pollen are notable locally at sites where these plants occur. Ericaceae values vary according to the type of sampling site. Cyperaceae and Sphagnum values fluctuate greatly depending on the proximity of these taxa to the sampling site. Pollen assemblages of the major taxa in six data sets extending from the forest-tundra of Saskatchewan to the eastern James Bay area in Québec were examined. Comparison yielded similar values of most genera. Local, regional and extra-regional influences, as well as over- and underrepresentation of individual taxa appear to apply uniformly over the entire area thereby providing pollen spectra representative of the forest-tundra of central Canada.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.037
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.220
Teacher spread0.191 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2011
Admission routes3
Has abstractyes

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