{"id":"W4402480488","doi":"10.1007/978-3-031-63402-4_36","title":"Candidate Performance Prediction—A Detailed Analysis Using Predictive Analytics Workbench","year":2024,"lang":"en","type":"book-chapter","venue":"Studies in systems, decision and control","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Workbench; Analytics; Computer science; Predictive analytics; Data mining; Data science; Visualization","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":[0.001182939,0.001458457,0.0009838978,0.002501016,0.0006319724,0.003044855,0.00146399,0.0006345251,0.01074613],"category_scores_gemma":[0.004489701,0.000394826,0.0009923952,0.002548326,0.0003789728,0.003147648,0.0007865945,0.001122218,0.003274809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006706144,"about_ca_system_score_gemma":0.0008322356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003266482,"about_ca_topic_score_gemma":0.002487649,"domain_scores_codex":[0.9991303,0.000123295,0.00003479823,0.000137096,0.0005032645,0.00007131634],"domain_scores_gemma":[0.997897,0.001270202,0.00009470413,0.000266187,0.0004245421,0.00004728679],"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":[0.0004642551,0.0003920352,0.0170852,0.0003260027,0.0001283408,0.0005265652,0.0002425666,0.2460627,0.01211676,0.06198051,0.01884362,0.6418314],"study_design_scores_gemma":[0.00001090337,0.0001791117,0.003452932,0.00005609637,0.00004802539,0.0001087757,0.0001257455,0.9587661,0.008071798,0.02310424,0.00603579,0.00004043053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0948181,0.001304209,0.8704883,0.0006451893,0.0001365403,0.0003248866,0.003415011,0.004487672,0.02438005],"genre_scores_gemma":[0.6407526,0.001368674,0.3267042,0.000145597,0.0001722298,0.00041607,0.006087941,0.0007495715,0.0236031],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01074613,"threshold_uncertainty_score":0.03594935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04109588983480728,"score_gpt":0.3064838129333459,"score_spread":0.2653879230985386,"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."}}