Bibliographic record
Abstract
Omeka 2.1 was released on August 27, 2013. Note: Due to an update to Zend Framework's requirements, Omeka 2.1 officially requires PHP version 5.2.11 or higher. New Features REST API GET, PUT, POST, and DELETE methods implemented for items, collections, files, item types, elements, and element sets. GET method available for users and tags. DELETE method available for tags. Enhancements Keyword search for users (#59) Direct links to plugin support_link sites (#258) Direct links to files from files/show (#542) record_url() now accepts query string parameters (#549) Added methods for on-the-fly changes to storage adapters (#550) Show tags for non-Item records in tags browse (#568) New get_record() helper for getting single records (#591, contributed by Jeremy Boggs) View object now automatically available for background processes (#593) Bugs Fixed Plugin versions were stored as type 'text' (#492) Too many plugins could make the bottom of the admin navigation unreachable (#519) Styling on admin files/show was overly restrictive for some content (#555) "does not contain" items advanced search was acting like "contains" (#588) Items advanced search was incorrectly excluding some results Plugin API New 'activate' and 'deactivate' plugin hooks (#349) New 'admin_collections_show_sidebar' hook (#520) Localization Strings to translate updated All languages updated Updated Libraries Zend Framework 1.12.3 getID3 1.9.6 pheanstalk 2.1.0 HTMLPurifier 4.5.0 jQuery 1.10.1 jQuery UI 1.10.3
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.224 | 0.302 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".