Bibliographic record
Abstract
Kulling, Monica. ZAP! Nikola Tesla Takes Charge. Illustrated by Bill Slavin. Tundra Books, 2016.In this, her ninth contribution to Tundra Books’ Great Ideas Series, prolific children’s author Monica Kulling distills and simplifies the life and inventions of immigrant engineer and scientist Nikola Tesla (1856–1943) for primary school readers. Confining her story to the first half of Tesla’s long life, from his humble origins in Slovenia (then a part of the Austro-Hungarian Empire), to his achievements as nineteenth-century America’s foremost electrical engineering genius, Kulling has maintained a manageable length compatible with the attention span of her audience.The rivalry between Tesla and his one-time patron and employer, Thomas Edison, over the suitability of alternating versus direct electrical current (AC vs. DC) is described without exposing all the sordid details of their rivalry. The story then quickly moves on to Tesla’s partnership with George Westinghouse to illuminate the 1892-93 Chicago world’s fair site, and to build the first hydroelectric power plant at Niagara Falls, employing alternating current, a system that allowed electricity to be transmitting over greater distances more cheaply and efficiently than Edison’s rival system. Kulling ends her story in 1898, when Tesla demonstrated a model boat controlled by radio waves, an invisible force that he suggested might also be used for wireless communication, a concept soon made real by radio pioneer Guglielmo Marconi.Apart from an anachronistic use of the word “robot,” Kulling’s text is historically and scientifically accurate, clearly written, and age-appropriate, without being condescending. Bill Slavin’s illustrations are nicely evocative of the late nineteenth-century buildings and workshops, and are scaled large enough for story-hour readings to groups of children.Reviewer: Merrill DistadHighly recommended: 4 out of 4 starsMerrill Distad is Associate University Librarian (Research and Special Collections Services) and University Archivist, University of Alberta, and is the co-editor of Peel’s Bibliography of the Canadian Prairies to 1953 (Toronto, 2003). He is the author, most recently, of The University of Alberta Library: The First Hundred Years, 1908–2008 (Edmonton, 2009).
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.741 | 0.633 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".