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2023· peer-review· en· W4323047633 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.

fundA Canadian funder is recorded on the work.
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

Venuenot available
Typepeer-review
Languageen
FieldEnvironmental Science
TopicHydrological Forecasting Using AI
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceMinistry of Science and Technology, TaiwanAcademia SinicaGlobal Lake Ecological Observatory Network
KeywordsTyphoonEnvironmental scienceDissolved organic carbonStratification (seeds)SubtropicsEcosystemHydrology (agriculture)MonsoonLake ecosystemOceanographyInflowEcologyGeology

Abstract

fetched live from OpenAlex

<strong class="journal-contentHeaderColor">Abstract.</strong> Extreme climates affect the seasonal and interannual patterns of carbon (C) distribution due to the regimes of river inflow and thermal stratification within lentic ecosystems. Typhoons rapidly load substantial amounts of terrestrial C into subtropical small lakes, renewing and mixing the water column. We developed conceptual dissolved C models and hypothesized that allochthonous C loading and river inflow intrusion may affect the dissolved inorganic C (DIC) and dissolved organic C (DOC) distributions in a small subtropical lake under these extreme climates. A two-layer conceptual C models was developed to explore how the DIC and DOC fluxes respond to typhoon disturbances on seasonal and interannual time scales in a small subtropical lake (i.e., Yuan‒Yang Lake) while simultaneously considering autochthonous processes such as algal photosynthesis, remineralization, and vertical transportation. Monthly field samplings were conducted to measure DIC, DOC, and chlorophyll <em>a</em> concentrations to compare the temporal patterns of fluxes between typhoon years (2015&ndash;2016) and non-typhoon years (2017&ndash;2018). The results demonstrated that net ecosystem production was 3.14 times higher in the typhoon years than in the non-typhoon years in Yuan‒Yang Lake. The results suggested that the load of allochthonous C was the most crucial factor affecting the temporal variation of C fluxes in the typhoon years; on the other hand, the transportation rate shaped the seasonal C in the non-typhoon years due to thermal stratification within this small subtropical lake.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.107
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0420.096

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 head0.070
GPT teacher head0.314
Teacher spread0.244 · 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

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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