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Record W2929877905 · doi:10.1002/star.201200125

Perspectives on the history of research on starch

2012· article· en· W2929877905 on OpenAlexaff
Koushik Seetharaman, Eric Bertoft

Bibliographic record

VenueStarch - Stärke · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsStarchDiastaseConfusionPolymer scienceChemistryFood sciencePsychology

Abstract

fetched live from OpenAlex

Abstract Starch has been used over several millennia for a number of different applications. However, research on understanding this substance only spans about three centuries starting with Leeuwenhoek who observed it in 1716. This story of discovery of the molecular structure and architectural makeup of starch is chronicled in a series of six essays of which this is the third with a focus on contemporary terminologies used in the 19th and early 20th centuries and its impact on advances in starch. Following the discovery of diastase, researchers focused on understanding the action of diastase on “transforming” starch into sugar. Besides maltose, they found that the products consisted of a range of dextrins with different abilities to complex with iodine. However, the nomenclature of the products that were obtained under a myriad of experimental conditions gave rise to confusions and misinterpretations, which transpired for over 30 years. Researchers also attempted to understand starch structure through systematic analyses of the different stages of starch breakdown. A new era of confusion in both nomenclature and structural interpretation started in the early 20th century with the discovery of cyclodextrins that were obtained from starch using the microorganism B. macerans . This gave rise to the school of “the low molecular elementary unit hypothesis” for starch structure, which lasted for about 25 years. magnified image Please read the Editorial for more details.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.078
GPT teacher head0.353
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2012
Admission routes1
Has abstractyes

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