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Record W2029935962 · doi:10.1080/08927010600602082

Bioassay-guided fractionation of antifouling compounds using computer-assisted motion analysis of brown algal spore swimming

2006· article· en· W2029935962 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiofouling · 2006
Typearticle
Languageen
FieldEngineering
TopicMarine Biology and Environmental Chemistry
Canadian institutionsUniversity of British Columbia
FundersNational Oceanic and Atmospheric AdministrationU.S. Department of CommerceNational Science Foundation
KeywordsBiofoulingFractionationSporeExtraction (chemistry)ChromatographyEnvironmental scienceChemistryBiologyBotany

Abstract

fetched live from OpenAlex

Antifouling extracts from the sea stars Astropecten articulatus and Luidia clathrata and from the brittle star Astrocyclus caecilia were fractionated by solid phase extraction and high performance liquid chromatography. Bioactive fractions were identified with the use of computer-assisted motion analysis-based bioassays utilising previously described Hincksia irregularis spore swimming behaviour parameters. Quantified parameters of spore movement were rate of change of direction (RCD) and speed (SPEE). The methods used initially required only 10 microg equivalent amounts of total crude extract and each resultant resolving step (normalised to 1 mg ml(-1) of crude, unfractionated extract) required far less material. Statistical analyses of RCD and ratios of RCD:SPEE values in experiments comparing swimming in the presence of extract fractions to controls revealed that both parameters were useful individually and in combination for efficiently following compound bioactivity throughout the fractionation procedure. This technique was also able to detect synergistic or additive interactions between compounds.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.016
GPT teacher head0.224
Teacher spread0.208 · 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