{"id":"W4251579429","doi":"10.21105/joss.03702","title":"BioPsyKit: A Python package for the analysis of biopsychological data","year":2021,"lang":"en","type":"article","venue":"The Journal of Open Source Software","topic":"Mental Health Research Topics","field":"Psychology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Deutsche Forschungsgemeinschaft","keywords":"Python (programming language); Computer science; R package; Programming language","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005410273,0.000132774,0.0005239392,0.0001388036,0.0002744505,0.00009221726,0.00402898,0.000102155,0.002765493],"category_scores_gemma":[0.001293331,0.00006674595,0.0002284483,0.001155473,0.0002374896,0.0001509917,0.001153257,0.000508832,0.00002270389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003950042,"about_ca_system_score_gemma":0.0001517336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001524331,"about_ca_topic_score_gemma":0.00007592779,"domain_scores_codex":[0.9972317,0.0009396677,0.0007408908,0.0002386343,0.0004832894,0.000365876],"domain_scores_gemma":[0.9939224,0.002909699,0.0006748899,0.001966251,0.0003816114,0.0001451818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006961074,0.002476123,0.06063751,0.0002484263,0.0154603,0.0003745964,0.01853788,0.0003077548,0.002241952,0.001780515,0.2251374,0.6658365],"study_design_scores_gemma":[0.006240334,0.001675034,0.4729881,0.0002539549,0.006787369,0.001343803,0.03185231,0.000669321,0.001014502,0.00225264,0.4743862,0.0005364733],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6836399,0.01658351,0.2583094,0.03232456,0.001926423,0.002672321,0.001749497,0.00004685884,0.00274743],"genre_scores_gemma":[0.9695261,0.0008322136,0.01410794,0.00340081,0.0006558509,0.00003810657,0.0001729089,0.00008194103,0.01118419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6653,"threshold_uncertainty_score":0.9981461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2909571309672493,"score_gpt":0.5151752410306641,"score_spread":0.2242181100634148,"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."}}