Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Colvild l1l9 palndlemlic lthlatl oclculrrledl alt lthle elndl olfl 2l01l9 which not only hladl an ilmplaclt on the world but also in Indonesia. Olnel olf lthlel tourist destinations that has experienced a very drastic decline is the Yogyakarta Smart Park. Taman Pintar Yogyakarta is an educational tourism vehicle destination lolcalteld lin tlhel clenltelr olf tlhel clitlyl olf Yogyakarta. Tlhle alpplrolaclh lusledl iln tlhils sltuldyl ils lal qluallitlatilvel alpprloalchl. Dlatla colllelctiloln telchlniqluels ulseld iln tlhils research include documentation techniques, interviews, observation and literature studies. lThle daltal anlallysils telchnliqluel ulseld lbly rleslearlchelrls luslesl tlhel Millels alndl Hulbelrmlanl moldell. Efforts made bly tlhel management of Taman Pintar Yogyakarta so that it can run effectively during the Covid-19 pandemic include carrying out internal and external activities, implementing health protocols, conducting counseling for employees. Yogyakarta Smart Park's strategy for dealing with the Covid-19 pandemic includes preparing SOPs, providing facilities and infrastructure, simulations and limited opening trials. The marketing strategies implemented by Taman Pintar Yogyakarta are plrilcel stlratlegyl, plrolmotliolnl sltrlatelgyl, pllalcle sltrlatlegyl alndl plroldulctl sltrlatleglyl.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.008 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it