Bibliographic record
Abstract
<JATS1:p>A 2022 Choice Reviews Outstanding Academic Title "Baseball fans actively following the sport in the 1990s and 2000s will greatly appreciate this fantastic book and its detailed insight." Library Journal Major League Baseball has had a long and storied history, but perhaps no era has been as competitive and unpredictable as the past 25 years, with an expanded postseason making for an unexpected and entertaining end to each season.</JATS1:p> <JATS1:p>In Americas Game in the Wild-Card Era: From Strike to Pandemic, Bryan Soderholm-Difatte provides a compelling examination of Major League Baseball since the 1994 players strike. He reveals how the last quarter century has been the most dynamic in MLB history and argues that bringing wild-card teams and the division-series round into the postseason mix have fundamentally changed how dynasties should be perceived. Following the major storylines for all 30 teams, along with the division races and state of dynasties over the past 25 years, Americas Game in the Wild-Card Era is a captivating look into a new age of baseball.</JATS1:p> <JATS1:p>Americas Game in the Wild-Card Era, together with Soderholm-Difattes Americas Game, Tumultuous Times in Americas Game, and The Reshaping of Americas Game, form the authors complete, definitive history of Major League Baseball.</JATS1:p>
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.000 |
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.
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; both teacher heads agree on what is shown here.
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".