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Record W2528409415 · doi:10.1111/jpy.12475

Consistency in a marine algal‐grazer interaction over multiple scales

2016· article· en· W2528409415 on OpenAlexafffund
Ladd E. Johnson, Robert T. Paine

Bibliographic record

VenueJournal of Phycology · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorGordon and Betty Moore FoundationNational Science Foundation
KeywordsBiologyConsistency (knowledge bases)EcologyOceanographyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Coralline algae are conspicuous members of many marine assemblages, especially those characterized by intense grazing pressure. We explored whether articulated species, especially Corallina vancouveriensis, depend on grazing invertebrates to both establish and flourish in an exposed rocky intertidal setting, and whether this plant-grazer relationship varied over more than three orders of magnitude (≈100->300,000 μm). Three experimental manipulations, supplemented by observations on recruitment, demonstrated that (i) C. vancouveriensis failed to recover rapidly from disturbed areas when grazers were experimentally excluded; (ii) recruitment occurred in the presence of grazers; (iii) increasing surface texture of molded surfaces enhanced coralline recruitment more when grazers were present; and (iv) settlement occurred predominately in microtopographical low areas of a molded surface, whereas a competitively superior fleshy red alga tended to recruit to high areas. These results confirm that coralline algal establishment and persistence are enhanced by grazers and reveal that this relationship is consistent over a range of biologically relevant scales.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.225
Teacher spread0.212 · 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

Citations9
Published2016
Admission routes2
Has abstractyes

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