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Record W2232729355

Debates in Canadian Family Physician

2006· article· en· W2232729355 on OpenAlexaboutno aff
Roger Ladouceur

Bibliographic record

VenueEurope PMC (PubMed Central) · 2006
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsViewpointsTask (project management)PoliticsTask forceMedicinePublic relationsPsychologyLawPolitical scienceManagement
DOInot available

Abstract

fetched live from OpenAlex

In medicine, there are few absolutes. It is not unusual for physicians with similar training and experience to have different points of view. Even when using rigorous scientific data, experts do not always agree and often reach different conclusions. Prestigious advisory bodies using the same data sometimes arrive at contradictory conclusions. For example, although they used the same data, the Canadian Task Force on the Periodic Health Examination and the United States Preventive Services Task Force issued different recommendations on use of mammography to systematically screen for breast cancer in women aged 40 to 49 years. Who has not heard the expression “Medicine is both an art and a science” to explain these differences? In light of these contradictions, Canadian Family Physician believes it is important to hear different points of view on topics of interest to family physicians. Consequently, we are launching a new column entitled “Debates.” This column will provide a forum for differing points of view or opposing positions on medical, political, or ethical issues. Topics must be of interest to family physicians, and the origin of the controversy must be clearly outlined. Debates will be structured as follows. Contributors holding opposing viewpoints will present their arguments in a “for” and “against” format on topics the journal deems relevant to family physicians. Texts must be short (maximum of 900 words each) and will be judged on the strength and logic of their authors’ arguments. A summary of the 3 key messages must be provided at the end of the piece. Texts will be published side by side in both official languages. Because authors will not know their opponents’ positions, they will have an opportunity to respond to these opponents’ comments (maximum of 500 words) in a subsequent issue. We hope that this new column will be of interest to you and that many of you will make your views known in letters to the editor. We want to hear from you!

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)0.021
metaresearch head score (Gemma)0.050
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.230
Threshold uncertainty score0.893

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.007
Science and technology studies0.0600.025
Scholarly communication0.0190.008
Open science0.0050.011
Research integrity0.0340.021
Insufficient payload (model declined to judge)0.0320.003

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 head0.028
GPT teacher head0.305
Teacher spread0.277 · 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
GenreCommentary

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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