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Heavy metals in burbot (Lota lota L.) caught in lakes of Northeastern Saskatchewan, Canada

2011· article· en· W1552592931 on OpenAlex
Allan H. K. Wong

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Applied Ichthyology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)FisheryCadmiumBiologyPolyunsaturated fatty acidHeavy metalsArsenicFood chainEnvironmental chemistryEcologyChemistryFatty acid

Abstract

fetched live from OpenAlex

Burbot could be a source of raw material for the commercial isolation of liver oil for a nutritional therapeutic product. Burbot liver oil have been found to contained high content of Vitamin D, Vitamin K and polyunsaturated fatty acids. It is also anticipated that the resulting burbot tissue would be commercial sold for human-food uses. The two target lakes, Athapapuskow Lake and Amisk Lake, of planned burbot catches are located downwind from a large copper–zinc smelter in Flin Flon, Manitoba, Canada. There was particular concern that burbot caught in these lakes may be contaminated with toxic heavy metals. Exploratory studies showed that the key toxic metals, viz., arsenic, cadmium, lead and mercury, were largely below the acceptable limits set forth in the guidelines of the Canadian Food Inspection Agency.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score0.977

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)0.0010.000

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 head0.018
GPT teacher head0.220
Teacher spread0.202 · 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