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Record W4238393566 · doi:10.1016/s0169-5002(12)00159-6

Contents

2012· paratext· de· W4238393566 on OpenAlexaff
Gary M. Sherman, Daniel I. Simon, Gill Lewin, Heonsu Jeon, Sanghyun Lee, Eun Ju Lee, Sungryul Yun, Fulong Tan, X. Y. Shen, Dongqi Wang, Guorui Xie, Xiang Zhang, Lu Ding, Yi Hu, Wei He, Yi Wang, Laura Morra, Markus Rechsteiner, Silvia Casagrande, Adriana von Teichman, Peter Schraml, H. Moch, Alex Soltermann, Guy Raz, Katharine A. Allen, Chris Kingsley, Irene Cherni, Sohrab Arora, Aprill Watanabe, Carles Lorenzo‐Bosquet, David A. Edwards, Sainetra Sridhar, Galen Hostetter, Glen J. Weiss, Greg Lee, Hyeongjin Lee, Y. Park, Ju Hee Lee, S Shanta, Hye‐Jeong Park, Carlijn van der Aalst, Harry J. de Koning, K Van Den Bergh, Marc C. Willemsen, Amy K. Ferketich, Gregory A. Otterson, Michelle A. King, Nathan C. Hall, Kristine Browning, Mark D. Wewers, Lee W. Jones, Whitney Hornsby, Amy Goetzinger, Lindsay M. Forbes, Emily L. Sherrard, Morten Quist, Amy R. Lane, M. West, Neil D. Eves, Margaret Gradison, April Coan, James E. Herndon, Amy P. Abernethy, Hyeyoung Ahn, Buxing Han, Tony Kiat Hon Lim, Jiangming Sun, Joonghyun Ahn, Myung‐Ju Ahn, Keun Park, Michael Lee, Sarah Kim, Jae Heon Jeong, Youngkwan Lee, Franco Pasqua, R D'angelillo, Francesca Mattei, Stefano Bonassi, Gian Luca Biscione, Katja Geraneo, V Cardaci, Luigi Ferri, S. Ramella, Pierluigi Granone, Silvia Sterzi, Ernesto Crisafulli, Enrico Clini, Filippo Lococo, L. Trodella, Alfredo Cesario, M De Boer, Aryan Vink

Bibliographic record

VenueLung Cancer · 2012
Typeparatext
Languagede
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.441
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.5590.366

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 head0.026
GPT teacher head0.349
Teacher spread0.322 · 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
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
Published2012
Admission routes1
Has abstractno

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