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Record W2796897305

Diet and Macronutrient Optimization in Wild Ursids: Grizzly Bears Versus Black Bears

2017· article· en· W2796897305 on OpenAlexaboutno aff
Cecily M. Costello, Steven L. Cain, Shannon Pils, Leslie Frattaroli, Mark A. Haroldson, Frank T. van Manen

Bibliographic record

VenueIntermountain journal of sciences · 2017
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsWonderWildlifeSection (typography)PopulationGeographyPolitical scienceLibrary scienceHistorySociologyEcologyPsychologyDemography
DOInot available

Abstract

fetched live from OpenAlex

At this 2017 meeting of the Northwest Section and the Montana Chapter of The Wildlife Society, this talk will present the past, present, and potential futures of the Northwest Section as it relates to Montana and to the Parent Society.  Many members today will remember the Section’s dedicated meetings and high level of professional involvement and wonder “where are we now?”    For others, this talk may be their introduction to the Section and how to be involved.  The Northwest Section has shared deep roots with our Montana wildlife heritage, with common leaders and common vision, since the inception of our profession.  Originally composed of Montana, Alaska, Oregon, Washington, Idaho, British Columbia, and Alberta, the Section had powerful and well-attended annual meetings with themes including foundational concepts in game bird and big game population and habitat management and policy.  Professionals representing an array of agencies, entities, and universities gathered to share the latest scientific findings, mentor students, and address environmental challenges.  A Parent Society reorganization in the early 2000’s lead to formation of a Canadian Chapter and the Section lost connection with British Columbia and Alberta.  Since that time, the Section has been through a period of reformation.  With well-represented member states, an enthusiastic board, and increased dues, the Section’s vision for the future is bright.  Future directions will include focus on building student chapters and bringing student conclaves to the Northwest, supporting policy stances on issues that cross state lines, and increasing communication between our member states.

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)0.000
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.053
GPT teacher head0.393
Teacher spread0.340 · 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
Published2017
Admission routes1
Has abstractyes

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