{"id":"W4392372617","doi":"10.1007/s12553-024-00836-9","title":"Dr. GPT will see you now: the ability of large language model-linked chatbots to provide colorectal cancer screening recommendations","year":2024,"lang":"en","type":"article","venue":"Health and Technology","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"IDELIX Software (Canada); McMaster University","funders":"","keywords":"Cancer; Colorectal cancer; Medicine; Computer science; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012211,0.0008960565,0.0006385362,0.001342785,0.001318119,0.0033379,0.00132305,0.005248338,0.05441948],"category_scores_gemma":[0.08391605,0.0005228315,0.0007409098,0.0004921601,0.0008927304,0.006188211,0.00264151,0.004819639,0.02067426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001084183,"about_ca_system_score_gemma":0.001321557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00414328,"about_ca_topic_score_gemma":0.008549685,"domain_scores_codex":[0.9948198,0.003266918,0.0002453066,0.0005077172,0.0008567597,0.0003036351],"domain_scores_gemma":[0.9234772,0.06165672,0.001366742,0.002275716,0.00585019,0.00537349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00205616,0.0006245083,0.01161531,0.0006735976,0.0001365987,0.0009705895,0.002591399,0.001201388,0.006216403,0.00210933,0.6478121,0.3239927],"study_design_scores_gemma":[0.001875696,0.004785895,0.02356118,0.00197005,0.0007177395,0.005884503,0.007988482,0.07097922,0.02573896,0.02641502,0.8289428,0.001140362],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.09479608,0.005980894,0.1055253,0.6622896,0.02029699,0.001285422,0.009000504,0.03975101,0.06107413],"genre_scores_gemma":[0.4909115,0.004763859,0.1711221,0.158294,0.008841434,0.001374916,0.006977065,0.005121294,0.1525938],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05441948,"threshold_uncertainty_score":0.1820513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02152960530507397,"score_gpt":0.3489072310691309,"score_spread":0.3273776257640569,"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."}}