MétaCan
Menu
Back to cohort
Record W1979426514 · doi:10.3137/ao.440204

Forcing mechanisms controlling surface and subsurface temperature anomalies along line‐p, North‐East Pacific Ocean

2006· article· en· W1979426514 on OpenAlexafffundvenueabout
Alexandre Laîné, William W. Hsieh, Howard J. Freeland

Bibliographic record

VenueATMOSPHERE-OCEAN · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsNorth Pacific Marine Science OrganizationUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCenters for Disease Control and Prevention
KeywordsDownwellingUpwellingWind stressGeologyForcing (mathematics)Submarine pipelineEkman transportOceanographySea surface temperatureClimatologyLine (geometry)Kelvin waveGeophysics

Abstract

fetched live from OpenAlex

Abstract The influence of different mechanisms on surface and subsurface temperature anomalies is considered along Line‐P, an oceanographic line extending from Vancouver Island into the Gulf of Alaska, which has been sampled for almost half a century. The role of a given mechanism is determined by applying canonical correlation analysis (CCA) between the anomalies of a parameter representing the mechanism and the Line‐P temperature anomalies. For each mechanism, it is determined if its direct influence can be detected, and if so, the domain of Line‐P over which it acts. Two areas along Line‐P, characterized by different forcing mechanisms, are identified: (1) offshore, west of 130°W, the main mechanisms influencing Line‐P temperature anomalies are the Ekman transport due to wind stress anomalies (with the zonal wind stress component somewhat more important than the meridional component) and wind mixing anomalies, (2) from the coast to 180 km offshore, coastal upwelling/downwelling anomalies and sea‐surface height anomalies along the coast of North America, resulting in coastal current anomalies and/or northward propagation of coastal waves, are important in determining Line‐P temperature anomalies.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.174
Teacher spread0.169 · 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 designObservational
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

Citations2
Published2006
Admission routes4
Has abstractyes

Explore more

Same venueATMOSPHERE-OCEANSame topicOceanographic and Atmospheric ProcessesFrench-language works237,207