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Record W4403958688 · doi:10.1086/733789

Demystifying Fundamental Theories in Ecology

2024· article· en· W4403958688 on OpenAlexaff
Rachel M. Germain, Sebastian J. Schreiber

Bibliographic record

VenueThe American Naturalist · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEcologyFeature (linguistics)BiologyPhilosophyLinguistics

Abstract

fetched live from OpenAlex

AbstractAs scientists, our collective goal is to make scientific progress in the pursuit of an absolute truth about the nature of the universe, through a feedback loop of observation, theory, and experimentation. What if a major limit to progress is not the science itself but rather in how broadly scientific ideas can be understood? In this introduction to a special feature, we highlight four articles, each tasked with demystifying a key theory in ecology for a general audience, with a special focus on aspects of each theory that have been misunderstood, misapplied, or underappreciated in some important way. These four theories are metabolic theory, competition theory based on consumer-resource models, mechanisms of coexistence in fluctuating environments, and metapopulation dynamics. We point out key ways in which each article applied best practices of accessible communication as well as challenges that might arise (and potential solutions for journals and authors) when attempting to publish articles with a deeper emphasis on explanation of fundamentals than a traditional article might provide.

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)0.000
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 score0.055
Threshold uncertainty score0.819

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.007
GPT teacher head0.268
Teacher spread0.261 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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