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Record W1974803448 · doi:10.1002/marc.201400563

Synthesis of Main‐Chain Metal Carbonyl Organometallic Macromolecules (MCMCOMs)

2015· review· en· W1974803448 on OpenAlexaff
Kai Cao, Nimer Murshid, Xiaosong Wang

Bibliographic record

VenueMacromolecular Rapid Communications · 2015
Typereview
Languageen
FieldChemistry
TopicSynthetic Organic Chemistry Methods
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMacromoleculeMetal carbonylOrganometallic chemistryGroup 2 organometallic chemistryMetalPolymerPolymer chemistryChain (unit)ChemistryPolymer scienceOrganic chemistryCatalysisMoleculePhysics

Abstract

fetched live from OpenAlex

Synthesis of main-chain metal carbonyl organometallic macromolecules (MCMCOMs) is difficult, mainly due to the instability of metal carbonyl complexes. Despite its challenge a number of MCMCOMs has been prepared by strategically using organometallic, organic, and polymer synthetic chemistry. Main contributions to this research field were reported by the groups of Tyler, Pannell, and Wang and are briefly summarized in this article.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.063
GPT teacher head0.339
Teacher spread0.275 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2015
Admission routes1
Has abstractyes

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