Soccer Stories: Matthew Arnone Interview (York 9FC/Canadian Premier League Soccer)
Bibliographic record
Abstract
Matthew Arnone talks about his time in Italy in Seria D with being Vegan, how he went from Striker to CB, his time at @HFXWanderersFC and @York9FC and more.   We first met Matthew when he was playing with the HFX Wanderers and we've been impressed with his skill and talent ever since. During the interview, we talked to Matthew about his upbringing, his time at TFC, playing in Italy and Vaughn, and his journey to the Wanderers. We also covered his switch to veganism, his new club York 9, and his Foundation "Jason's Wish" in honour of his brother.  As you listen to Matthew and his story, you are really struck by his kindness, mindfulness, not only to his dedication to the sport of soccer but also to live the best and happiest life he can. So get ready, get comfortable, and have a listen to this in-depth interview with Matthew Arnone! You can follow Matthew and his soccer journey with York9 here: https://www.instagram.com/arnonematthew23/ https://twitter.com/arnonematthew23 Full timestamps on our website. --- Send in a voice message: https://podcasters.spotify.com/pod/show/soccerstories/message
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.547 | 0.010 |
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".