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Record W4213094948 · doi:10.53607/wrb.v26.149

Case Study: A Split–brood Comparison of Formula for Nestling Songbirds (FoNS ) versus Three Facility–specific Diets

2008· article· en· W4213094948 on OpenAlexaff
Lani D. Sheldon, Anna Drake

Bibliographic record

VenueWildlife Rehabilitation Bulletin · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsBiologySturnusBroodZoologyFeatherSparrowAnimal scienceStarlingCorvidaeFledgePasserineEcologyHatching

Abstract

fetched live from OpenAlex

Thirty–four nestling birds of seven species were used to test whether Formula for Nestling Songbirds (FoNS ) would result in better weight gain, feather growth, and survival rates compared to inexpensive control diets. Ten broods, of 2 to 5 birds, were split into two groups. Some of each brood received FoNS while others received one of three species specific and facility–formulated control diets. Four species (Bewick’s wren [Thryomanes bewickii], red–eyed vireo [Vireo olivaceus], violet–green swallow [Tachycineta thalassina], and black–capped chickadee [Poecile atricapillus]), received a control diet consisting of dog food supplemented with bone meal, brewer’s yeast, and protein powder. With the exception of the swallows, birds on this control diet generally lost weight, and three of the five died; whereas all six birds from the same broods survived and gained weight on FoNS . Two species, (house sparrow [Passer domesticus] and house finch [Carpodacus mexicanus]) received control diets of chick starter with cat food, hard boiled eggs, bone meal powder, and peanut butter, and one species (European starling [Sturnus vulgaris]) received a control diet based on dog food. For these species, the FoNS diet and control diets showed similar development, growth, and no deaths. The authors suggest that FoNS diet is advantageous, especially for small, insectivorous species, but some inexpensive alternatives may be equally suitable for certain species.

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 score0.032
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.061
GPT teacher head0.308
Teacher spread0.247 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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