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Record W2095480980 · doi:10.1007/s12192-012-0320-z

Ferruccio Ritossa’s scientific legacy 50 years after his discovery of the heat shock response: a new view of biology, a new society, and a new journal

2012· article· en· W2095480980 on OpenAlexaffabout
Antonio De Maio, Massimo Santoro, Robert M. Tanguay, Lawrence E. Hightower

Bibliographic record

VenueCell Stress and Chaperones · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSerendipityHeat shockShock (circulatory)Scientific discoveryIdentification (biology)CuriositySession (web analytics)BiologyHistoryHeat shock proteinNeuroscienceComputer scienceCognitive sciencePhilosophyPsychologyMedicineEpistemologyEcologyGeneticsWorld Wide Web

Abstract

fetched live from OpenAlex

The pioneering discovery of the heat shock response by the Italian scientist Ferruccio Ritossa reached maturity this year, 2012. It was 50 years ago that Professor Ritossa, through an extraordinary combination of serendipity, curiosity, knowledge and inspiration, published the first observation that cells could mount very strong transcriptional activity when exposed to elevated temperatures, which was coined the heat shock response. This discovery led to the identification of heat shock proteins, which impact many areas of current biology and medicine, and has created a new avenue for more exciting discoveries. In recognition of the discovery of the heat shock response, Cell Stress Society International (CSSI) awarded Professor Ritossa with the CSSI medallion in October 2010 in Dozza, Italy. This article is based on a session of the Fifth CSSI Congress held in Québec commemorating Professor Ritossa and his discovery.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0060.003

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 head0.021
GPT teacher head0.277
Teacher spread0.256 · 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 designNot applicable
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

Citations71
Published2012
Admission routes2
Has abstractyes

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