Bibliographic record
Abstract
New concentrations of job opportunities in the hinterland of Prague Abstract In the past 40-50 years in North America and is currently also in some European regions we can see within the frame of suburbanisation process creation of new centers in the hinterland of the main cities. The development of these nuclei greatly influences the spatial structure of metropolitan areas. The aim of this work is to try to identify new concentrations of job opportunities in Prague hinterland which could be described as indedependent or cutting adrift and in this respect prove certain similarity to the metropolitan regions westward of the Czech Republic. Observation will be mainly applied to the development of the number and structure of job opportunities in the selected villages. These indicators will be helpful to identify the new concentration of jobs in the Prague metropolitan area. Subsequent analysis of commuting to work in selected villages partly answers the question of how the commuting links between elements of the Prague metropolitan area have changed and whether there is a noticeable trend towards the creation of new centers, which would include also non-residential functions, such as significant offer of an employment and services. In the case study of one selected municipality will be subsequently followed up...
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".