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Record W7098318487

the Shortgrass Library System (SLS).

2016· article· en· W7098318487 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemistry
TopicChemical synthesis and alkaloids
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipPatienceNational libraryInformation systemExtension (predicate logic)
DOInot available

Abstract

fetched live from OpenAlex

Becoming a member library of Shortgrass means that DDPL patrons now have a larger collection of materials to choose from. DDPL patrons will be able borrow from any of the Shortgrass member libraries, including Brooks and Medicine Hat without having to pay a non-resident fee. This will save some families up to $80 per year. Plus, they can have their selections delivered right to DDPL for pickup, without charge. Not only will DDPL patrons have access to all Shortgrass materials, but as part of a regional system they will be able to borrow from any library in Alberta. There will be a transition phase over the next few months, involving the logistics of providing DDPL patrons access to all of the SLS resources. The patience of DDPL patrons will be especially appreciated during this period. In joining SLS, Sandra Peers the DDPL Board Chair remarked, “pooling resources makes sense. By entering this partnership we just increased the collection available to local patrons by about 100 times.” “The expanded services for the library that comes from being a part of Shortgrass, are great for area residents, ” adds Wayne Dahl, a Duchess Councilor and member of

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.571
Threshold uncertainty score0.815

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.4290.164

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 head0.005
GPT teacher head0.171
Teacher spread0.166 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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Same topicChemical synthesis and alkaloidsFrench-language works237,207