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Advances in spatial, individual‐based modelling of forest dynamics

2004· article· en· W4241415242 on OpenAlex
Richard T. Busing, Daniel Mailly

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

VenueJournal of Vegetation Science · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsMinistère des Ressources naturelles et des Forêts
Fundersnot available
KeywordsPropaguleCanopyPatch dynamicsSpatial ecologyForest dynamicsEcologyTree (set theory)Vegetation (pathology)Common spatial patternComputer scienceEnvironmental scienceEcosystemMathematicsBiology

Abstract

fetched live from OpenAlex

Abstract Many individual‐based models of forest dynamics lack spatial complexity. Although, in certain cases, spatially simple models may not be substantially inferior to spatially complex models, advances in vegetation science indicate potential weaknesses, particularly the lack of consideration of propagule availability in horizontal space, and varying patch (or canopy gap) dimensions. Models with vertical and horizontal spatial complexity can address these issues, but, thus far, evidence that they outperform patch (or gap) models is limited. Comparison of projections from models that differ only in their spatial complexity is needed to address the effects of propagule availability in space, spatial pattern of canopy tree mortality, and spatial resolution.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.187

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.274
Teacher spread0.253 · 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