Corrigendum: Borealization of the Arctic Ocean in Response to Anomalous Advection From Sub-Arctic Seas
Bibliographic record
Abstract
Corrigendum on: Polyakov IV, Alkire MB, Bluhm BA, Brown KA, Carmack EC, Chierici M, Danielson SL, Ellingsen I, Ershova EA, Gårdfeldt K, Ingvaldsen RB, Pnyushkov AV, Slagstad D and Wassmann P (2020) Borealization of the Arctic Ocean in Response to Anomalous Advection From Sub-Arctic Seas. Front. Mar. Sci. 7:491. doi: 10.3389/fmars.2020.00491In the original article, there was an error. The description of the method used to calculate the depth of the lower boundary of the halocline is not complete.A correction has been made to Section 3 "Methods," Sub-section "a. Methods in physical observations," paragraph "Halocline base depth": Halocline base depth: For each CTD and ITP profile the lower halocline boundary is defined following Bourgain and Gascard (2011) who show that the density ratio Rr = (a ¶q/ ¶z)/(b ¶S/ ¶z) = 0.05 (a is the thermal expansion coefficient and b is the haline contraction coefficient, q is potential temperature and S is salinity) may be used to identify the cold halocline base depth.This algorithm is used in Figs. 12, 13. The depth of the 0 o C isotherm defines the total halocline base depth; it is used in all other figures where the depth of the halocline base is required ( Figs. 7, 8, 14, 15, and S7).The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.119 | 0.083 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".