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Record W202088985

Proceedings of a workshop on research strategies into the causes of declining Atlantic salmon returns to North American rivers

2000· article· en· W202088985 on OpenAlexaboutno aff
S O'Neil, John A. Ritter, Kimberly A. Robichaud-LeBlanc

Bibliographic record

VenueScholarWorks@UMassAmherst (University of Massachusetts Amherst) · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFisheryGeographyBiology
DOInot available

Abstract

fetched live from OpenAlex

In response to the decline in the abundance of Atlantic salmon returning to rivers in North America and limited directed research programs on salmon at sea, Fisheries and Oceans Canada convened a special workshop to define a research strategy and to lay the groundwork for an intensive and integrated research campaign. The workshop took place from June 12 to 14, 2000 at the Dalhousie University in Halifax Nova Scotia, with participants from government agencies in Canada, United States (New England) and Europe, as well as Canadian Universities and the Atlantic Salmon Federation. The workshop format included a plenary session for introducing the subject, terms of reference, and a brief overview of background material, followed by division of participants into three working groups defined by the life stage of Atlantic salmon (freshwater, estuarine/nearshore, and marine). Each subgroup was assigned the tasks of reviewing the most plausible reasons for the salon's decline and ranking research programs on the basis of likelihood of success, feasibility, and fundability. Products from the workshop include 15 project proposals summarizing the background information, databases necessary to test hypotheses, time frame for completion, resources required, and the value of the proposal related to the consequences for better understanding the decline in salmon. In addition, this Proceedings document was produced to archive the activities and discussions during the meeting.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.026
GPT teacher head0.265
Teacher spread0.238 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2000
Admission routes1
Has abstractyes

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