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Record W4406917325 · doi:10.18778/1427-9711.23.04

Zarastanie i zanikanie najmniejszych jezior na Niżu Polskim

2024· article· pl· W4406917325 on OpenAlexaff
Rajmund Skowron, Artur Zieliński, Tomasz Jaszczyk

Bibliographic record

VenueActa Universitatis Lodziensis Folia Geographica Physica · 2024
Typearticle
Languagepl
FieldEnvironmental Science
TopicIntegrated Water Resources Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Praca jest kontynuacją badań autorów nad procesami zarastania oraz zmian powierzchni jezior położonych na obszarze Niżu Polskiego. Analizą objęto 590 jezior o powierzchni do 100 ha, dla których sporządzono dane dotyczące zarastania i zanikania, oparte o materiały przedstawione przez Instytut Rybactwa Śródlądowego (IRŚ) w Olsztynie za lata 1958–1968 oraz dane zawarte w Katalogu jezior Polski (Choiński 2006) i zbiorach Centralnego Ośrodka Dokumentacji Geodezyjnej Kartograficznej (CODGiK), w postaci ortofotomap pochodzących z lat 2010–2012. Porównanie danych zawartych w wyżej wymienionych źródłach wskazują na zmiany powierzchni oraz stopnia zarastania roślinnością wynurzoną w grupie badanych jezior. Celem pracy było określenie stopnia przeobrażeń akwenów, jakie zaszły w okresie ostatniego półwiecza. Rezultaty obliczeń wykazują, że powierzchnia 590 jezior zmniejszyła się aż o 6,3 km2, czyli aż o 11,6%, natomiast współczynnik zarastania podwyższył się o 0,6%.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.002

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.

Opus teacher head0.006
GPT teacher head0.202
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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