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Record W3010189346 · doi:10.3171/2019.12.focus19859

The initial experience of InterSurgeon: an online platform to facilitate global neurosurgical partnerships

2020· article· en· W3010189346 on OpenAlexaff
Jacob Lepard, S. Hassan A. Akbari, Faizal Haji, Matthew C. Davis, William Harkness, James M. Johnston

Bibliographic record

VenueNeurosurgical FOCUS · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeneral partnershipEnthusiasmSession (web analytics)Duration (music)MedicineFamily medicineBusinessPsychologyFinanceAdvertisingSocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Despite general enthusiasm for international collaboration within the organized neurosurgical community, establishing international partnerships remains challenging. The current study analyzes the initial experience of the InterSurgeon website in partnering surgeons from across the world to increase surgical collaboration. METHODS: One year after the launch of the InterSurgeon website, data were collected to quantify the number of website visits, average session duration, total numbers of matches, and number of offers and requests added to the website each month. Additionally, a 15-question survey was designed and distributed to all registered members of the website. RESULTS: There are currently 321 surgeon and institutional members of InterSurgeon representing 69 different countries and all global regions. At the time of the survey there were 277 members, of whom 76 responded to the survey, yielding a response rate of 27.4% (76/277). Twenty-five participants (32.9%) confirmed having either received a match email (12/76, 15.8%) or initiated contact with another user via the website (13/76, 17.1%). As expected, the majority of the collaborations were either between a high-income country (HIC) and a low-income country (LIC) (5/18, 27.8%) or between an HIC and a middle-income country (MIC) (9/18, 50%). Interestingly, there were 2 MIC-to-MIC collaborations (2/18, 11.1%) as well as 1 MIC-to-LIC (1/18, 5.6%) and 1 LIC-to-LIC partnership. At the time of response, 6 (33.3%) of the matches had at least resulted in initial contact via email or telephone. One of the partnerships had involved face-to-face interaction via video conference. A total of 4 respondents had traveled internationally to visit their partner's institution. CONCLUSIONS: Within its first year of launch, the InterSurgeon membership has grown significantly. The partnerships that have already been formed involve not only international visits between HICs and low- to middle-income countries (LMICs), but also telecollaboration and inter-LMIC connections that allow for greater exchange of knowledge and expertise. As membership and site features grow to include other surgical and anesthesia specialties, membership growth and utilization is expected to increase rapidly over time according to social network dynamics.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.844
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.275
GPT teacher head0.375
Teacher spread0.100 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations42
Published2020
Admission routes1
Has abstractyes

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