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Record W7135742394

Czechs and Slovaks in the first season of the second century NHL

2019· dissertation· cs· W7135742394 on OpenAlexaboutno aff
Kamila Majerová

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2019
Typedissertation
Languagecs
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsSlovakCzechTheme (computing)Ice hockeyWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

Title: Czechs and Slovaks in the first season of the second century of NHL Abstract The theme od the thesis are Czechs and Slovaks in the first season of the second century of NHL. The main aim of my work is to analyze the course of the season 2017-2018. In my work I will focus on the Czech and Slovak players and their comparison with players from the other European countries and with USA and Canada ice hockey superpowers. The comparison will be focused on the number of players, Canadian points, players' productivity in the 2017 NHL Entry Draft, their average age, and the players' age versus productivity. I will also focus on the team statistics (representation of Czechs, Slovaks and Europeans in each team). Key words Ice hockey, NHL, ice hockey players, Czechs, Slovaks, Europeans, goals, points

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0050.001
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.007
GPT teacher head0.198
Teacher spread0.191 · 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
Published2019
Admission routes1
Has abstractyes

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