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Record W2139865725 · doi:10.5376/ijms.2014.04.0053

Identification and assess anthropogenic impacts on species richness of coral reef fishes in Larak Island, Persian Gulf

2014· article· en· W2139865725 on OpenAlex
Khatami Sh.

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Marine Science · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCoral reefPersianSpecies richnessIdentification (biology)CoralReefFisheryEnvironmental issues with coral reefsGeographyOceanographyEcologyEnvironmental scienceGeologyBiology

Abstract

fetched live from OpenAlex

Coral reefs are amongst the most important and rich ecosystems in the world and are provide habitat for a diverse range of species groups of fishes and invertebrates. Larak Island is one of fourteen islands found in the Persian Gulf which was selected for this study. The reef fish distribution around this island was identified and then for sampling, six stations were randomly selected by Manta Tow method. The identification was conducted using visual census technique in all stations. A total of 54 species belonging to 42 genera and 23 families were identified and amongst them the abundant species group belonged to family Pomacentridae with 11 species. The results indicated that further the stations were from an urban area higher species richness was.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.250

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.014
GPT teacher head0.264
Teacher spread0.250 · 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