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Record W7095883236

Regeneration and reproduction of Mazzaella cornucopiae (Rhodophyta,

2015· article· en· W7095883236 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
Fundersnot available
KeywordsFrondQuadratPruningBiomass (ecology)Intertidal zoneReproductionAbundance (ecology)
DOInot available

Abstract

fetched live from OpenAlex

The effects that different intensities of frond harvesting have on frond regeneration and subsequent production of reproductive structures were investigated for the red intertidal alga Mazzaella cornucopiae (Postels & Ruprecht) Hommersand from British Columbia, Canada. Harvesting was done by pruning fronds in the late spring (when stand biomass is highest) of 1993 at two intensities: total and partial collection of fronds, in this second case leaving all frond biomass less than 1 cm high in place. Holdfasts were not damaged. Total percent cover of thalli, frond density, mean frond length, and stand biomass for these experimental quadrats were statistically similar to values for control quadrats in the spring of 1994. These results suggest that one total harvest of fronds per year, done in late spring without damaging holdfasts, may give the highest sustainable yield of biomass. The effects of harvesting intensity on reproduction were variable and difficult to explain. Neither the appearance nor the abundance of cystocarpic fronds were affected by frond pruning, compared with control areas, but pruning did affect the appearance and the abundance of tetrasporic fronds. Partial pruning resulted in a longer presence of tetrasporic fronds, whereas total pruning was associated with their complete absence. Results are compared with those for the few other species of the Gigartinaceae for which experimental harvesting has been done.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.030
GPT teacher head0.205
Teacher spread0.175 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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