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Record W4229377809 · doi:10.55968/uniaca.2022.11.2.5

PAST & PRESENT SCENARIO OF BASKETBALL IN RELATION TO OLYMPICS

2022· article· en· W4229377809 on OpenAlexaboutno aff
Pratibha Takotra

Bibliographic record

VenueInternational Journal of Research Pedagogy and Technology in Education & Movement Sciences · 2022
Typearticle
Languageen
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsBasketballPopularityMedalAdvertisingPeriod (music)AthletesEvent (particle physics)PsychologyHistorySocial psychologyBusinessPhysical therapyAestheticsArtMedicine

Abstract

fetched live from OpenAlex

Sports and games became a focal point in establishing a strong relationship wherever we lived. It is a familiar and comfortable venue for connection with each other because sport is a complex activity, which become a sort of war on human muscles and mind. We have witnessed a revolution in the wide arena of sports. Basketball is a highly competitive game and it demands high physical qualities. The prime physical qualities are explosive strength, strength endurance, agility, speed, various coordinative abilities, etc. Height without fitness or technical ability without endurance becomes a liability. In all court games, including Basketball, fast starts, sudden stops, and quick change in direction are basic to good performance. Everybody knows that Basketball is a game which requires high degree of movement, and the players should be physically fit to have a control over the game. Basketball was introduced in the olympic programme at the 1904 games in St Louis an a demonstration event. Basketball was first contested as a medal event at the 1936 olympics. Women’s basketball meanwhile made its debut at the montreal 1976 games. Start from the origin in 1891 in springfield, Massachusetts the game achieved almost immediate acceptance and popularity. In 1936 it also introduced in Olympics and plays a better version itself. USA dominated basketball olympics. However Indian basketball team scripted history by qualifying summer olympics in Moscow . After that period the performance of team started diminishing till now the uplift does not reaches the height forthcoming performance of indian team excel in future and touches the new sky.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.173
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.133
GPT teacher head0.581
Teacher spread0.448 · 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 teacher head, 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

Citations2
Published2022
Admission routes1
Has abstractyes

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