{"id":"W2323373872","doi":"10.1177/1553350614537562","title":"The Impact of Marketing Language on Patient Preference for Robot-Assisted Surgery","year":2014,"lang":"en","type":"article","venue":"Surgical Innovation","topic":"Global Healthcare and Medical Tourism","field":"Health Professions","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University Health Network; University of Toronto","funders":"","keywords":"Medicine; Preference; Surgery; Robot; Artificial intelligence; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004288909,0.00009443633,0.0002226755,0.0000772914,0.0003716317,0.000004726046,0.00007601301,0.0001612421,0.00006582392],"category_scores_gemma":[0.005347857,0.00005287223,0.00009040959,0.0005117278,0.00004082245,0.0000313649,0.00002953392,0.0003074231,0.00001452521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00010933,"about_ca_system_score_gemma":0.0002070521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000299145,"about_ca_topic_score_gemma":0.00001477838,"domain_scores_codex":[0.9976028,0.0009182682,0.0007144578,0.0001502138,0.0002439345,0.0003703499],"domain_scores_gemma":[0.9911169,0.007750995,0.000394673,0.0002069489,0.000461005,0.00006945808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001481991,0.0001258641,0.0079408,0.0002667777,0.00002910304,0.000002271167,0.0003441699,0.00001180804,0.0003165985,0.01364312,0.07423119,0.9016063],"study_design_scores_gemma":[0.001528098,0.0007859854,0.7956182,0.001204683,0.00001277111,0.000002531246,0.0007679249,0.001157894,0.0002658799,0.002300347,0.1960996,0.0002560374],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836003,0.00005089158,0.0003254346,0.001607038,0.0005616916,0.0006096674,0.00002033321,0.00004231301,0.01318231],"genre_scores_gemma":[0.9984848,0.00002108052,0.0000854795,0.0003843572,0.0002986532,0.0001085159,0.00008304137,0.000009863723,0.0005242014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9013503,"threshold_uncertainty_score":0.640227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.136529040268027,"score_gpt":0.4662205762571764,"score_spread":0.3296915359891495,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}