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Record W7153672063

Game Laws for 1910

2024· article· W7153672063 on OpenAlexaboutno aff
J. A. Allen

Bibliographic record

VenueDigital Commons - University of South Florida (University of South Florida) · 2024
Typearticle
Language
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsnot available
FundersNorthwestern University
KeywordsEleventhScheduleFood supplyState (computer science)Supply and demandAgriculture
DOInot available

Abstract

fetched live from OpenAlex

McAtee's 'Plants Useful to Attract Birds and Protect Fruit.'--Attention is here called "to the plants which best serve to provide food for birds and to draw their attention away from cultivated crops."A list of the species of native plants most resorted to for food by birds is given.From this list species can be selected for cultivation which will afford both shelter and a continuous supply of food, including some which retain their fruit through the winter and furnish a food supply at seasons when bird food is hardest to obtain.Food plants are suggested for various groups of birds, and for different regions.The mulberry is recommended as unsurpassed for alluring birds from early orchard fruits.There are also suggestions for providing water and favorable haunts, as well as food, and for the protection of birds from cats and other predatory animals.--J. A. A. Game Laws for 1910. 2 --This is the eleventh annual summary of the game laws of the United States and Canada, and reviews the laws which passed, and which failed to pass, during 1910, together with a schedule of open seasons, and the regulations respecting the shipment and sale of game, and the obtaining of licenses for hunting and shipping, under the Federal and State laws of the United States, and the orders in council of the Canadian Provinces.These annual digests are of great importance and convenience as a source of definite information for sportsmen and game protectors, and form a valuable record of progress in bird and game protection.-

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.002
Science and technology studies0.0020.005
Scholarly communication0.0000.003
Open science0.0030.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.228
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueDigital Commons - University of South Florida (University of South Florida)Same topicDoping in SportsFrench-language works237,207