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Record W2172136828 · doi:10.1007/s10144-010-0242-5

Comments on Brodie and Post: Climate‐driven declines in wolverine populations: causal connection or spurious correlation?

2010· article· en· W2172136828 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.

Bibliographic record

VenuePopulation Ecology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsMinistry of Environment
Fundersnot available
KeywordsSnowpackSnowSpurious relationshipProxy (statistics)EcologyPopulationBiologyGeographyDemographyStatisticsMeteorologyMathematics

Abstract

fetched live from OpenAlex

Abstract The recent paper by Brodie and Post (“Nonlinear responses of wolverine populations to declining winter snowpack”, Popul Ecol 52:279–287, ) reports conclusions that are unsupportable, in our opinion, due to both mis‐interpretations of current knowledge regarding the wolverine's ( Gulo gulo ) association with snow, and the uncritical use of harvest data to index wolverine populations. The authors argue that, because the wolverine is a snow‐dependent species, average annual provincial snowfall, based on weather station data, can be expected to correlate strongly and positively with wolverine population numbers, which in turn can be accurately indexed by trapper harvests. Thus, correlations between declines in wolverine harvests and declining average snowpack are interpreted to reflect a climate‐driven decrease in wolverine populations. This conclusion overstates the nature of the wolverine's association with snow, and makes unsupportable assumptions about the reliability of harvest data as a proxy for population size.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.999

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)0.0020.000

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 head0.018
GPT teacher head0.276
Teacher spread0.258 · 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