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Record W3032569534 · doi:10.29173/bluejay5609

Results of the 2008 International Butterfly Count in Saskatchewan

2008· article· en· W3032569534 on OpenAlexaffvenueabout
Mike Gollop, Anna Leighton

Bibliographic record

VenueBlue Jay · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsButterflyGeographyBiologyEcology

Abstract

fetched live from OpenAlex

Nine International Butterfly Counts (1JC) were conducted in Saskatchewan in 2008, the same as in 2007 and one more than in 2006.Counts in 2008 were conducted at Bjorkdale, Fort Qu'Appelle, Last Mountain Lake National Wildlife Area, Nisbet Forest, Pasquia Hills, Preeceville, Regina, Saskatoon and Waskesiu River.The Waskesiu River count was last conducted in 2006.Duck Mountain Park was the only count done in 2007 that was not repeated in 2008.Count statistics are presented in Table 1, and count results in Table 2.There were 66 species recorded in 2008 compared to 60 in 2007,62 in 2006 and 57 in 2005.12 3 The total number of butterflies counted was 4983 compared to 4007 in 2007, 3669 in 2006, and 6972 in 2005, of which 5389 were Painted Ladies.Butterflies per party-hour (ph) is used as a measure to relate butterfly numbers to observer effort so as to provide a comparable index of abundance over years.Butterflies per party-hour was 62 in 2008 for the nine counts compared to 48 in 2007 and 2006 and 86 in 2005, although again, if Painted Ladies are removed from the 2005 count, the butterflies per party-hour would be only 27.It appears from this that overall numbers of butterflies were up in 2008 but such provincial averaging may mask local results.In general the more southerly counts and those held earlier in the year had significantly fewer butterflies than did the later counts along the forest fringe.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.619

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.008
GPT teacher head0.203
Teacher spread0.194 · 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 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

Citations0
Published2008
Admission routes3
Has abstractyes

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