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Record W7024874485

Texas Navigator App

2021· article· en· W7024874485 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks @ UTRGV (The University of Texas Rio Grande Valley) · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsnot available
Fundersnot available
KeywordsTSG101PretextLimitingCircumstantial evidenceParaphernaliaGloom
DOInot available

Abstract

fetched live from OpenAlex

On Google Maps you can get navigator voices in English with either an American, British, Indian, or Canadian accent. I think they should offer a Texas navigator accent. We’ll call the navigator Jim Bob. Of course he couldn’t just have the accent. He’d need Texas expressions and colloqualisms too. Jim Bob would give you guidance something like this: You’re fixin’ to wanta take the ramp for Dallas up yonder ‘bout half a mile. You might oughta get in the left line right quick. Now, if you miss your exit, Jim Bob will say, Where you goin’? Missed your exit back there. It don’t matter. I’ll fix it. Grab the exit onto the feeder road and then take the Texas turn around. That’ll head you north and we’ll be back in business. Up the road a piece you’re gonna come to a four-way stop. You’ll see a Dairy Queen catty-cornered to you there. Take a left. You can ask questions of Jim Bob, like how far to Marfa? Tell you what, that’s not the question to ask. It’s a fur piece out there. What you wanta ask is how many HOURS to Marfa? From Brownsville, 10 hours. Unless you wanta take the scenic route, then I’d just say tomorrow. Any Starbucks ’round here Jim Bob? Nope. But, you got a great BBQ restaurant just a mile down that dirt road to your left. Down home and authentic BBQ. Plenty of ice cold Shiner Bock and Big Red too. Jim Bob, is this the right road to Dallas? Yep, best way. You’re already headed north on I-35. Just stay on it. Don’t give up. You’ll get there eventually – but you’ll likely be as frazzled as a kitten in a cactus patch when you arrive. In settings you can select surly Jim Bob. He begins most responses with “Do what now?” Jim Bob, what’s the traffic like in Austin? Do what now? What do you think it’s like? Same as always. A slow-moving train wreck. It’s got more bottle necks than Jack Daniels. Jim Bob, how far is it from Beaumont to El Paso? Do what now? I’d be ashamed to ask that question if was I you! How can you not know that? How long you been in Texas anyway? Also available in settings: Jim Bob, navigator … and life coach. Jim Bob, how fast can I get to Sixth Street? You know its 1:30 a.m.? Your mama wouldn’t want you goin’ over there this time of night. I’m not gettin’ between you and your mama and you shouldn’t either. Jim Bob, could you plot a course to Chicago? What do you want to go there for? Tell you what, nothing but cold up there this time of year. Nothing up there you can’t get here in Texas anyway, except for unbearable cold. Yup. I think we need a Texas accent navigator, to have Jim Bob along even outside of Texas, guiding you up Rodeo Drive in Hollywood, along Rockefeller Center in Manhattan or by the Washington Monument in Washington, D.C. Those warm Texas tones would be like comfort food far away from home. Hey, Google. You listenin’?

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.191
Teacher spread0.186 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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