Internet page content analysis of north European Sea ports
Bibliographic record
Abstract
Abstract This study analyses 98 Internet pages of sea ports located in Sweden, Finland and Estonia during years 2017–2019. Aim of the study is to find, how website basic design is completed (colours and languages), how slogans, environmental issues, statistics and hinterland transports are reported. Based on the analysis, it appears as rather common that sea ports follow conservative selection of colours in their websites, where blue and white are clearly most popular. Typically, English and Swedish are as the most common used language, followed by Finnish, Russian and Estonian. In some rare cases, websites are offered in Chinese or German. Larger sea ports do have clear “slogans”, where smaller ones are just having lengthy justification for their existence. Environmental issues are increasing concern among sea ports, and these are mostly mentioned in details within Swedish actors. Providing statistics varies among companies, and in some sea ports these are provided from very long time period, where in others from just previous years or then only from last year (or even at all). It is common for companies to report that they have sustainable hinterland access, railway available.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".