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Record W1986801377 · doi:10.1517/14656566.7.4.489

Multidisciplinary Symposium on Head and Neck Cancer

2006· article· en· W1986801377 on OpenAlexaff
Mark Agulnik, Lillian L. Siu

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2006
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineHead and neck cancerHead and neck squamous-cell carcinomaHead and neckOncologyChemoradiotherapyCancerDiseaseChemotherapyMultidisciplinary approachCarcinogenesisInternal medicineSurgery

Abstract

fetched live from OpenAlex

The Multidisciplinary Symposium on Head and Neck Cancer focused on the emerging data that underlie optimal treatment for head and neck cancers, with a particular focus on squamous cell carcinoma of the head and neck. In-depth discussions showcased the published Phase II and Phase III data on the treatment of locally advanced disease with both induction chemotherapy and concurrent chemoradiotherapy. Molecular targets of interest and relevance in this tumour type were identified, as were the agents which target these putative proteins or pathways of carcinogenesis. Preliminary results from trials incorporating molecularly-targeted agents have shown a promising role for these compounds in the management of both locally advanced and recurrent/metastatic squamous cell carcinoma of the head and neck. The Symposium brought a clear message. The management of squamous cell carcinoma of the head and neck has evolved considerably, and with the advent of newer chemotherapeutic agents and molecularly targeted therapies, this field will continue to expand over time.

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)0.002
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: none
Teacher disagreement score0.059
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0590.022

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 head0.040
GPT teacher head0.403
Teacher spread0.363 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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