Bibliographic record
Abstract
A Gamer’s Introduction to Programming with MonoGame: Welcome Brave Adventurer! is a great way to combine your current love of both video games and coding into a brand‑new love of writing your own games. In this book, you’ll learn the essential ins‑and‑outs of how to work with fonts and text, images and sprites, audio, and even animation. You’ll learn how to give your players control over their destiny through keyboards, mice, and gamepads, and you’ll harness the never‑ending energy of the gameplay loop functions. But coding books are technical, boring, and scary, aren’t they? Not this one. Within these pages, you’ll find a fun and approachable adventure that will introduce you to the accessible but powerful MonoGame development framework. Using Visual Studio and C#, you’ll write simple but engaging interactive scenes and games that will gradually build up your coding skills and confidence. Packed with practical examples, plain‑language explanations, images, and illustrations, this book is structured like a video game, complete with levels to progress through, cutscenes to give you extra information, and final challenge projects to show you how everything fits together and to help build your own creative portfolio. It is also the second book in an ongoing series designed to take you from zero experience to writing your own video games and interactive digital experiences using industry standard languages and tools. For readers with previous object‑oriented programming experience, this book is a standalone introductory MonoGame adventure. Gain even more experience by exploring the resources, bonus materials, and extensive code samples available at the companion website: https://welcomebraveadventurer.ca. Now, gather your courage and prepare to level up by joining the MonoGame coding quests that await you inside.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, 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".