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Record W2960312428 · doi:10.1242/jeb.190470

The good, the bad and the slimy: experimental studies of hagfish digestive and nutritional physiology

2019· review· en· W2960312428 on OpenAlexafffund
Chris N. Glover, Alyssa M. Weinrauch

Bibliographic record

VenueJournal of Experimental Biology · 2019
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicInsect symbiosis and bacterial influences
Canadian institutionsAthabasca UniversityUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHagfishPhysiologyBiologyZoologyBiochemistryVertebrate

Abstract

fetched live from OpenAlex

The hagfishes provide valuable insight into the physiology of feeding, digestion and nutrient absorption by virtue of unusual and unique features of their biology. For example, members of this group undergo long periods of fasting, and are the only vertebrates known to absorb organic nutrients across their epidermal surface. Such properties engender significant attention from researchers interested in feeding and feeding-related processes; however, the practical realities of employing the hagfish as an experimental organism can be challenging. Many of the key tools of the experimental biologist are compromised by a species that does not readily feed in captivity, is difficult to instrument and which produces copious quantities of slime. This Commentary provides critical insight into the key aspects of hagfish feeding and digestive processes, and highlights the pitfalls of this group as experimental organisms. We also suggest key research gaps that, if filled, will lead to better understanding of hagfishes, and we consider how this group may advance our knowledge of feeding, digestion and nutrient absorption processes.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.067
GPT teacher head0.346
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2019
Admission routes2
Has abstractyes

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