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Record W2032586774 · doi:10.1515/bot.2007.010

Diversity, abundance and distribution of macroalgae at Sirinart Marine National Park, Phuket Province, Thailand

2007· article· en· W2032586774 on OpenAlexaff
Pimonrat Thongroy, Lawrence M. Liao, Anchana Prathep

Bibliographic record

VenueBotanica Marina · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsUniversity of Prince Edward Island
FundersUniversity of Arizona
KeywordsIntertidal zoneAbundance (ecology)ShoreSargassumDiversity indexNational parkSpecies diversityGeographyEcologyBiodiversitySalinityRocky shoreFisheryBiologyAlgaeSpecies richness

Abstract

fetched live from OpenAlex

Abstract Diversity, abundance and distribution of intertidal macroalgae were investigated in relation to environmental conditions (site, shore level, salinity, temperature, NO 3- and ) in Sirinart Marine National Park, Phuket province, Thailand, from January to November 2004. The shores were divided into 3 categories by shore level: upper, mid and lower shores; and 3 sampling sites: sites 1, 2 and 3. A total of 52 species of macroalgae were recorded. Nine species are considered to be new records for the Thai marine flora. The average diversity index of macroalgae differed slightly among sites: 0.92±0.07 (mean±SE), 1.00±0.13 and 0.94±0.16 for site 1, site 2 and site 3, respectively. There was significant difference in abundance of macroalgae among sites and seasons. Lyngbya majuscula and Padina australis were the most abundant species. Their percentage covers were 31.66±7.21% and 27.77±4.67% in site 2 at mid shore level during March 2004 and in site 3 at mid shore level during November 2004, respectively.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.011
GPT teacher head0.201
Teacher spread0.190 · 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

Citations17
Published2007
Admission routes1
Has abstractyes

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