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Record W4389656416 · doi:10.1002/ecs2.4137

Cover Image

2023· paratext· en· W4389656416 on OpenAlexaboutno aff

Bibliographic record

VenueEcosphere · 2023
Typeparatext
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsEcologyEctothermForesterCover (algebra)Global warmingGeographyPopulationClimate changeBiologyDemography

Abstract

fetched live from OpenAlex

COVER PHOTO: The Rocky Mountain tailed frog (Ascaphus montanus) inhabits cold, fast-flowing streams in the northern Rocky Mountains of the United States of America and Canada. Plasticity in thermal physiological traits, such as heat tolerance, may be an important component of vulnerability to warming temperatures for this cold-tolerant species, as well as other ectotherms. As such, estimates of plasticity in these traits must accurately reflect physiological coping capacity. By quantifying heat tolerance plasticity among populations of Rocky Mountain tailed frogs and its sister species, coastal tailed frogs (A. truei), Cicchino et al. (Ecosphere, Volume 14, Issue 11, Article e4691; doi: 10.1002/ecs2.4691) demonstrate the impacts of population variation and experimental design on inferences of species vulnerability to warming. Photo credit: Brenna Forester.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaInsufficient payload (model declined to judge)
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
gptInsufficient payload (model declined to judge)
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models agreeAgreement compares identical category sets and study designs across arms.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.003
Threshold uncertainty score0.857

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)0.9920.994

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 head0.021
GPT teacher head0.256
Teacher spread0.236 · 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

Labeled directly by 2 models reading the full record.

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueEcosphereSame topicSpecies Distribution and Climate ChangeCategoryInsufficient payload (model declined to judge)French-language works237,207