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Record W2737622906 · doi:10.15200/winn.150038.82260

Science AMA Series: I’m Dr. Adrian Owen, a neuroscientist whose research focuses on brain imaging, cognitive function and consciousness. We’re finding new ways to decode the complex workings of the brain. AMA.

2017· dataset· en· W2737622906 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Winnower · 2017
Typedataset
Languageen
FieldPsychology
TopicParanormal Experiences and Beliefs
Canadian institutionsnot available
Fundersnot available
KeywordsConsciousnessPsychologyBrain functionCognitionCognitive scienceNeuroscience

Abstract

fetched live from OpenAlex

I’m Dr. Adrian Owen, a professor of neuroscience, here to answer your questions about our breakthroughs in brain science. I’ve been fascinated with the human brain for more than 25 years: how it works, why it works, what happens when it doesn’t work so well. At the Owen Lab at Western University in Canada, my team studies human cognition using brain imaging, sleep labs, EEGs and functional MRIs. We’ve learned that one in five people in a vegetative state are actually conscious and aware (I recently wrote a book on it – www.intothegrayzone.com, if you’re interested). We’ve also examined whether brain-training games actually make you smarter (pro tip: they don’t). Now my team is working on a cool new project to understand what happens to specific parts of people’s brains when they get too little sleep. We’re testing tens of thousands of people around the world to learn why we need sleep, how much we need, and the long- and short-term effects sleep loss has on our brains. A lot of scientists and influencers, such as Arianna Huffington and her company Thrive Global, have already raised awareness about the dangers of sleep loss and the need for research like this. Since we can’t bring everyone to our labs, we’re bringing the lab to people’s homes through online tests we’ve designed at www.worldslargestsleepstudy.com or www.cambridgebrainsciences.com. We hope to be able to share our findings in science journals in about six months. So … if you want to know about sleep-testing, brain-game training or how we communicate with people in the gray zone between life and death … AMA! I will be here at 1:00pm EDT (10:00am PDT / 5:00pm UTC), with researchers from my lab, Western University and the folks who host the www.worldslargestsleepstudy.com platform—ask me anything! Update: We’re here now! Ask us anything! Proof that I am real: http://imgur.com/a/NvPMK Update 2: I appreciate all the questions! I tried my best to answer as many as I could. This was really fun. See you next time. Now, time for some pineapple pizza! http://imgur.com/a/Yy88r

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.683
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.006
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.140
GPT teacher head0.429
Teacher spread0.289 · 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