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Record W2990534470 · doi:10.1515/pac-2019-1014

The 24<sup>th</sup> IUPAC International Conference on Physical Organic Chemistry (ICPOC 24)

2019· article· en· W2990534470 on OpenAlexaboutno aff
Maria L. S. Cristiano

Bibliographic record

VenuePure and Applied Chemistry · 2019
Typearticle
Languageen
FieldChemistry
TopicInorganic and Organometallic Chemistry
Canadian institutionsnot available
FundersFundação Luso-Americana para o DesenvolvimentoUniversidade do PortoCentro de Ciências do MarUniversidade de CoimbraUniversidade do MinhoUniversidade de Aveiro
KeywordsChemistryChemical nomenclatureEnvironmental chemistryOrganic chemistryRadiochemistryPhysical chemistry

Abstract

fetched live from OpenAlex

The IUPAC sponsored biennial Conference on Physical Organic Chemistry (ICPOC) series bear a long history and a solid reputation as the leading international gatherings on Physical Organic Chemistry. Since their first installment in Crans sur Sierre (Switzerland) in 1972, ICPOC meetings have been held in Noordwijkerhout (The Netherlands, 1974), Montpellier (France, 1976), York (UK, 1978), Santa Cruz (USA, 1980) Louvain-la-Neuve (Belgium, 1982), Auckland (New Zealand, 1984); Tokyo (Japan, 1986), Regensburg (Germany, 1988), Haifa (Israel, 1990), Padua (Italy, 1994), Incheon (Korea, 1996), Florianopolis (Brazil, 1998), Göteborg (Sweden, 2000), San Diego (USA, 2002), Shanghai (China, 2004), Warsaw (Poland, 2006), Santiago de Compostela (Spain, 2008), Busan (Korea, 2010), Durham (UK, 2012), Ottawa (Canada, 2014), Sidney (Australia, 2016). The 24st IUPAC International Conference on Physical Organic Chemistry (ICPOC 24) was held at the University of Algarve, in Faro, Portugal, July 1–6, 2018.

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)0.004
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.057
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0060.004
Open science0.0030.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0570.047

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 head0.008
GPT teacher head0.214
Teacher spread0.207 · 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
GenreOther

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

Citations4
Published2019
Admission routes1
Has abstractyes

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