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Record W4385536059 · doi:10.1515/9780773586796

Leave No Doubt

2012· book· en· W4385536059 on OpenAlexaboutno aff
Mike Babcock, Rick Larsen

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2012
Typebook
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Mike Babcock is the only hockey coach in the history of the game to lead teams to victory in the Stanley Cup, the World Championship, and the Olympic Games. Formerly the head coach for the Detroit Red Wings for ten seasons, and now the head coach for the Toronto Maple Leafs, he is arguably the best coach in the game today. In this book, against the dramatic backdrop of the Canadian men's gold medal victory in Vancouver, Babcock provides an inspiring roadmap for achieving goals and fulfilling dreams. This is not just a book about hockey but a book about life, rooted in Babcock's "Leave No Doubt" credo. Written by Babcock and his longtime friend Rick Larsen, the credo hung on Team Canada's dressing-room wall during their historic run to Olympic gold. It provides a compelling framework for excelling in life. Illuminated by revealing stories about overcoming doubt, "owning pressure," and making a difference, "Leave No Doubt" is based on a firm belief in everyday commitment and a step by step approach to being "better than good enough." The words originally written for Canada's Olympic gold medal hockey team - leave no doubt, every day counts, our determination will define us - inspire an approach to succeeding in life that is relevant to people of all interests and ambitions. Athlete or not, each of us will find valuable guidance in this succinct primer from one of the most respected leaders in sports.

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)0.003
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.388
Threshold uncertainty score0.873

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.005
Scholarly communication0.0170.012
Open science0.0020.008
Research integrity0.0090.013
Insufficient payload (model declined to judge)0.3880.340

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 head0.027
GPT teacher head0.241
Teacher spread0.215 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2012
Admission routes1
Has abstractyes

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