{"id":"W4404494219","doi":"10.1145/3674658.3674687","title":"Assessing Patient Eligibility for Inspire Therapy through Machine Learning and Deep Learning Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Deep learning; Artificial intelligence; Machine learning","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007685686,0.0002518931,0.0002608467,0.0001021731,0.0005755642,0.001077611,0.0003199021,0.0001136012,0.00002328787],"category_scores_gemma":[0.0001983779,0.0002051277,0.00009716751,0.0003635595,0.00004651699,0.001739761,0.0002785019,0.0008033541,0.000006670292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008377348,"about_ca_system_score_gemma":0.00009200695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004555633,"about_ca_topic_score_gemma":0.00003253187,"domain_scores_codex":[0.9976429,0.0003302008,0.0003837022,0.0008801568,0.0003150913,0.0004479369],"domain_scores_gemma":[0.9986499,0.0007119502,0.00009271422,0.0003165841,0.0001196182,0.0001092331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000113055,0.00002853395,0.007683469,0.0002648151,0.0000254487,0.00001010589,0.006231417,0.02084475,0.00009975286,0.05250798,0.00001979527,0.9122726],"study_design_scores_gemma":[0.0002410423,0.0003256407,0.0004273126,0.00008148327,0.000003575404,0.00001948975,0.000180161,0.9565198,0.0001280493,0.01598117,0.02585189,0.0002403543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1049257,0.01144489,0.8764752,0.002137859,0.0003459299,0.0004647008,9.44137e-7,0.001215768,0.002989038],"genre_scores_gemma":[0.8953841,0.0004998423,0.1033275,0.0004163556,0.00007034591,0.00005576861,0.00000913984,0.00003536556,0.0002015156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9356751,"threshold_uncertainty_score":0.9999593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06677967952671057,"score_gpt":0.3761381871395605,"score_spread":0.30935850761285,"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."}}