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Record W4293201576 · doi:10.1155/2022/5917198

[Retracted] Infrared Spectroscopic Measurement of Dissolved Organic Matter and Nanomaterials in Water Based on Parallel Factor Algorithm

2022· article· en· W4293201576 on OpenAlexaboutno aff
Li Liang

Post-publication record

NatureRetraction
ReasonConcerns/Issues about Data;Concerns/Issues about Referencing/Attributions;Concerns/Issues about Peer Review;Investigation by Journal/Publisher;Investigation by Third Party;Unreliable Results and/or Conclusions;
Date8/2/2023 0:00
Flagged by OpenAlex?Yes

Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.

Bibliographic record

VenueJournal of Nanomaterials · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsnot available
FundersNatural Science Foundation of Chongqing
KeywordsDissolved organic carbonColored dissolved organic matterEstuaryEnvironmental scienceOceanographyEnvironmental chemistryGeologyChemistryEcologyBiology

Abstract

fetched live from OpenAlex

Infrared spectroscopy can separate carbon sugars and amino sugars that have collapsed in soil water very quickly. In this study, the midinfrared (MIR) and near‐infrared (NIR) spectra collected from soil water isolates or soil masses are sentenceless, assessing different agricultural groupings of flooded carbon and aminosaccharides. Soil was collected from five fields in two regions in western Canada and two regions in eastern Canada, where least squares backslide (PLSr) was inadequate. The inverted model of DOC recovery at the Eastern Peace River estuary can provide the optical functionality of traditional systems. The introduction of overflow DOCs from various sources rather than distance meters has been found to be a major contributor to the complexity of optical neighborhoods, resulting in a bias in DOC evaluation. The impact of voluntary DOC liability on the relationship between DOC and CDOM can be forgotten at a critical turn in the CDW. A slightly mitigating approach can overlook the impact of voluntary DOC responsibility on the relationship between DOC and CDOM. CDW is responsible for the continued responsibility of the Subei coastal currents for the normal material of the former Yellow Sea Delta, for the warm West Coast currents of the Yellow Sea for the materials of the Yellow Sea, and for the materials of the Changjiang Basin. The results of this study more thoroughly assess the state differences of DOM inputs from different sources within the CDW to determine the magnitude of the impact on DOC evaluation across the East China Sea CDOM. It suggests that it is necessary.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0330.022

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 head0.016
GPT teacher head0.229
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designBench or experimental
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

Citations1
Published2022
Admission routes1
Has abstractyes

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