MétaCan
Menu
Back to cohort
Record W3009793767 · doi:10.1016/0967-0653(95)99639-9

10.1016/0967-0653(95)99639-9

2000· article· en· W3009793767 on OpenAlexvenueno aff
H. M. Mostafa, Ken Collins

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsSea urchinParacentrotus lividusCadmiumZincCopperOceanographyMediterranean seaSeawaterFisheryBiologyMediterranean climateChemistryEcologyGeology

Abstract

fetched live from OpenAlex

Abstract Sea urchins (Paracentrotus lividus) were collected from the Mediterranean coast off Alexandria, Egypt and the Atlantic coast of Ireland to the west of Galway. Samples of another urchin species, Psammechinus miliaris, were collected from the entrance to Southampton Water, U.K. Both the Alexandria coast and Southampton Water receive domestic and industrial waste water inputs whilst the western Irish coast is relatively unpolluted. Sampled animals were dissected to separate coelomic fluids, Aristotle's lantern, gonads and tissue (digestive tract plus connective tissue). the concentrations of heavy metals (cadmium, copper, lead, nickel and zinc) in the different parts were measured using flame atomic absorption spectroscopy. Many levels of heavy metals in the different parts were similar in specimens taken across the wide range of sites and the two species. A notable exception was the high level of copper (33 μg g−1 dry wt.) and zinc 328 μg g−1− dry wt.) in urchin tissue from Southampton Water. The m...

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0040.005
Open science0.0030.004
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.9890.990

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 head0.010
GPT teacher head0.218
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

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueTime to knitSame topicPublic Health and NutritionFrench-language works237,207