Dictionary of basic indexing terminology: Polish and Czech; Słownik podstawowej terminologii indeksacyjnej: polski i czeski; Slovník základní terminologie indexování: polský a český
Bibliographic record
Abstract
The dictionary of basic indexing terminology is now expanding to include two Slavic languages – Polish and Czech. This article provides a list of common indexing terms in Polish and Czech, along with their English equivalents. It also gives readers a brief introduction to elements of Polish and Czech grammar that may be relevant when indexing. In particular, it gives an overview of the use of plurals, orthography and alphabetization, and indexing style in Polish- and Czech-language books. Słownik podstawowej terminologii indeksacyjnej poszerza się obecnie o dwa języki słowiańskie – polski i czeski. W tym artykule zamieszczono listę popularnych terminów indeksowanych w języku polskim i czeskim wraz z ich angielskimi odpowiednikami. Zawiera także krótkie wprowadzenie do elementów gramatyki polskiej i czeskiej, które mogą mieć znaczenie podczas indeksowania. W szczególności daje przegląd użycia liczby mnogiej, ortografii i alfabetyzacji oraz stylu indeksowania w książkach polsko- i czeskojęzycznych. Slovník základní indexační terminologie se nyní rozšiřuje o dvě slovanské jazyky – polština a čeština. Tento článek obsahuje seznam běžných indexačních termínů v angličtině, polštině a češtině. Čtenářům také stručně představuje prvky polské a české gramatiky, které mohou být při indexování relevantní. Zejména podává přehled o používání množného čísla, pravopisu, abecedním řazení a stylu indexování v polsky a česky psaných knihách.
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 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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.025 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.029 |
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".