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Record W7035975264

Ancient clam gardens increased production: Adaptive strategies from the past can inform food security today

2013· other· en· W7035975264 on OpenAlexfundaboutno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2013
Typeother
Languageen
FieldComputer Science
TopicCloud Computing and Resource Management
Canadian institutionsnot available
FundersParks CanadaNational Geographic Society
KeywordsIntertidal zoneProductivityEcosystemHabitatBiomass (ecology)Food securityMaricultureAdaptive strategiesForagingMarine habitats
DOInot available

Abstract

fetched live from OpenAlex

Maintaining food production while sustaining productive ecosystems is among the central challenges of our time, yet it has been for millennia.We quantified the productivity of ancient clam gardens, intertidal rock-walled terraces made by humans, by comparing the biomass and density of surveyed bivalves and growth rates of transplanted Leukoma staminea (littleneck clams) at replicate clam garden and non-walled beaches in British Columbia, Canada.We found that clam gardens had significantly shallower slopes, significantly greater densities of L. staminea and Saxidomus giganteus, and higher growth of transplanted L. staminea.As predicted, productivity varied as a function of tidal height, beach position and size class.Consequently, we provide strong empirical and experimental evidence that ancient clam gardens likely increased clam productivity by altering beach slope, expanding optimal intertidal habitat thereby enhancing growing conditions for clams.These results reveal how a traditional form of mariculture can inform resilient food security strategies today.

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 score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.010
GPT teacher head0.180
Teacher spread0.170 · 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

Citations1
Published2013
Admission routes2
Has abstractyes

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