{"id":"W7070479385","doi":"","title":"Patiëntenvoorkeuren om de waarde van gentherapie te bepalen","year":2020,"lang":"en","type":"article","venue":"Lirias (KU Leuven)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Orphan drug; Health technology; Value (mathematics); Quality of life (healthcare); Preference","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001761692,0.000221576,0.0001969633,0.00002667329,0.00009360397,0.00004713306,0.0003882796,0.0002062729,0.0002502017],"category_scores_gemma":[0.0002004755,0.000210629,0.0001383953,0.0000927064,0.00006034059,0.000006881435,0.0001805508,0.0002499117,0.0002411298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001986814,"about_ca_system_score_gemma":0.00008275047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000239105,"about_ca_topic_score_gemma":0.00001779103,"domain_scores_codex":[0.9987723,0.00009276599,0.0002906143,0.0002923195,0.0001831067,0.0003688576],"domain_scores_gemma":[0.9991937,0.00001832143,0.0001317555,0.0003903522,0.0000501415,0.0002157222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001265439,0.0004490713,0.1446838,0.0007435484,0.001534271,0.0001058936,0.01488582,0.009690241,0.3916817,0.001875394,0.2096288,0.223456],"study_design_scores_gemma":[0.001088234,0.0005847843,0.003769589,0.00002432451,0.00004950686,0.00002514505,0.0002550259,0.006038135,0.03012129,0.0001488099,0.9574055,0.0004896706],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9494458,0.001311443,0.01601223,0.01022213,0.0004304138,0.0005113735,0.00008732167,0.00020004,0.02177921],"genre_scores_gemma":[0.9837463,0.0001216673,0.005127226,0.008657863,0.0008224577,0.00001801363,0.0002180815,0.00005427229,0.001234113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7477767,"threshold_uncertainty_score":0.8589203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01194734801582336,"score_gpt":0.2418595530003709,"score_spread":0.2299122049845475,"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."}}