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Record W2928466079 · doi:10.2110/palo.2018.040

BIORESUSPENSION BEHAVIORS OF THE GOBIID, <i>VALENCIENNEA PUELLARIS,</i> AND THE BIOGENIC SEDIMENTARY STRUCTURES IT PRODUCES

2019· article· en· W2928466079 on OpenAlexaff
Reed A. Myers, Murray K. Gingras, GABRIELLA KEYES, Kurt O. Konhauser, John‐Paul Zonneveld

Bibliographic record

VenuePalaios · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine Biology and Ecology Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCitationIconDownloadHistoryLibrary scienceGeologyArchaeologyArt historyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

ABSTRACT Biologically mediated fabrics are disturbed sediment by organisms that resemble primary physical structures. In this aquaria-based study, the sand-sifting goby, Valenciennea puellaris, produced biogenic sedimentary structures resembling planar lamina and ripple cross lamina with grain sizes ranging from fine sand to gravel. Valenciennea puellaris moved and re-deposited fine- and coarse sand and gravel used in this study, but dug only in fine- to coarse sand. Gravel-sized particles were too large to pass through its gills and therefore the goby moved them individually. Through the bioresuspension behaviors of feeding, digging, and resting, the V. puellaris produces Piscichnus-like craters and moves about nine mouthfuls of sediment a minute, i.e., 0.18 cm3. The biogenic fabrics produced by V. puellaris in this study are similar to primary sedimentary fabrics produced by hydrologic flow. Similar behaviors and feeding styles are widespread and found in larger fish and marine mammals. While V. puellaris has only been around since the Eocene, burrowing Actinopterygians date back to 400 Ma, suggesting that similar biogenic sedimentary structures may have a long history in the geological record.

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 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 categoriesInsufficient payload (model declined to judge)
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 score0.999

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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 teacher head, not a consensus.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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