MétaCan
Menu
Back to cohort
Record W2966208233 · doi:10.15173/sciential.v1i2.2136

Immortal Hydra as a Model Organism for Metal Toxicity Studies

2019· article· en· W2966208233 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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueSciential - McMaster Undergraduate Science Journal · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine Invertebrate Physiology and Ecology
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsLernaean HydraOrganismToxicityMetal toxicitySimplicityBiologyModel organismToxicologyMedicine

Abstract

fetched live from OpenAlex

Toxicology is an interdisciplinary scientific field that explores the impact, epidemiology, and treatment regimens for exposure to various toxic compounds and elements. Many toxicants such as metals have not yet been comprehensively examined, and a plethora of metal-related conditions are currently untreatable. Hydra is an immortal freshwater organism that serves as an excellent model for toxicity studies due to its natural availability, anatomical simplicity, yet comparatively complex physiology. This review will examine the significance of hydra toxicity studies, outline current experimental designs, as well as summarize the most commonly tested metals. Altogether, comprehensive toxicity studies on Hydra might provide promising breakthroughs in the understanding of toxicity-related physiology, and can be applied to clinical research and practice to ultimately improve health and wellbeing of those affected by metal-related disorders.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.025
GPT teacher head0.274
Teacher spread0.249 · 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