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Record W2908748138 · doi:10.1353/rvt.2018.0022

Earthquakes and Angels

2018· article· en· W2908748138 on OpenAlexaboutno aff
Sydney Lea

Bibliographic record

VenueRiver teeth · 2018
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPicnicMidnightYardCoveEveningNoticeHistoryArchaeologyArtCartographyArt historyGeographyLaw

Abstract

fetched live from OpenAlex

Earthquakes and Angels Sydney Lea (bio) So there I was, training for a flat-water kayak race near our beloved camp in Washington County, Maine. August of 2016, a great interlude in my life: I was seventy-four, but to churn the water for two hours at a time and to feel strong enough meanwhile that I could notice the lavish splendors of the neighborhood—well, it all but gave me the illusion that I'd never grow truly old. I could maintain racing speed at the same time as I noted, say, a cow and calf moose plunging their heads into Picnic Cove for its plentiful spatterdock. I'd hear loons shriek when eagles soared into sight, so great a bane has the resurgence of these raptors proven to their young. One evening, the wind entirely in my favor, I passed within yards of a young coyote as it drank from Oxbrook Lake. Waterborne, I could dream that landlubber deerflies and mosquitoes were mere figments of fancy. The race was canceled for fear of lightning. A good thing, maybe, because two weeks after its scheduled date I had a heart attack. Insofar as my symptoms didn't closely resemble any I'd read or heard about, when I visited the tiny clinic in Calais, the nearest facility to our [End Page 15] remote cabin, I was more than surprised at the blood test's indication of ischemia. Within a few hours, I'd arrived by ambulance at Eastern Maine Medical Center to have a stent placed in my occluded right coronary artery. Three weeks thereafter, I found myself in rehab, pedaling a stationary bike and hauling on a rowing machine, keeping my heart rate at 120 to 130 beats per minute for three quarters of an hour at a time, feeling better than I had back when I didn't know there was anything wrong with me except for a geezer's occasional stiff back and his ever more creaky knees. Almost exactly a year after my crisis, I entered the 2017 race and came in third. Of course a win would have been more gratifying; on the other hand, the ages of the two men who beat me, combined, amounted to less than my own, and I established a personal best for the course. I was a lucky bastard, and am. One reason for my adopting a passion for the two-bladed paddle over a decade ago lay, precisely, in the slow degeneration of those knees. For a few years, with the aid of plenty of Tylenol, I could still hike reasonably well, but less and less could I do so with the unmixed pleasure of older times. My response was ever more avidly to practice the kayak regime, which entails no impact. Again, there's the benefit that, especially when there's a bit of covering breeze, my progress remains quiet enough that I witness all manner of natural wonders. Back home, I'll never forget the eagle, for example, who, as I plied the Connecticut River, stooped so hard onto a Canada goose that the poor bird might have been shot: a faint quiver or two, and then utter stillness in the corpse. As the predator tore at breast-meat, savvy ravens drifted into the cottonwoods, waiting their turns—patient, soundless. I recall thinking, scarcely for [End Page 16] the first time, How do they know? They always do, all but immediately. Uncannily. Black bear and blackbird. Otter and osprey. Beaver and bittern. Nighthawk and newt. Wood duck and wood turtle. I could go on. ________ My thoughts here, however scattered, are motivated by the notion, precisely, of new knees, the first replacement slated for ten days hence. At my sanest, I'm aware how blessed I've been, particularly as a lover of the outdoors, to live how and where I do, and thus, again and again, even as my undercarriage has made fun of me, to witness so many wonders, natural and otherwise. I also understand the advantages of existing in a medical era when procedures like the one I face have become pretty routine. Lord, nowadays the medicos can actually print your 3...

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.058
GPT teacher head0.430
Teacher spread0.372 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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