{"id":"W4237986666","doi":"10.1016/s0167-739x(04)00046-9","title":"BioSim?a biomedical character-based problem solving environment","year":2004,"lang":"en","type":"article","venue":"Future Generation Computer Systems","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"School of Computer Science, Carnegie Mellon University; Universität zu Köln; Simon Fraser University","keywords":"Computer science; Human–computer interaction; Morphing; Domain (mathematical analysis); Process (computing); Abstraction; Artificial intelligence; Programming language","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000114335,0.0001723658,0.0001489422,0.000109041,0.00006658621,0.00009091813,0.0001133691,0.0001324875,0.00002165771],"category_scores_gemma":[8.496864e-7,0.0001532083,0.00004389669,0.0001303929,0.00001884615,0.00008856618,0.00001342704,0.0001358609,0.0001086263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00017136,"about_ca_system_score_gemma":0.00002985953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007465333,"about_ca_topic_score_gemma":9.171706e-7,"domain_scores_codex":[0.9990283,0.00001689422,0.000283049,0.0002052347,0.0002452009,0.0002212828],"domain_scores_gemma":[0.9996064,0.000007257399,0.0000301763,0.0001916285,0.00001690318,0.0001476266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002314297,0.0001932111,0.00002983086,0.0008754238,0.00008596398,0.00001375701,0.0007352448,0.7478044,0.04599335,0.001065074,0.1903652,0.01283626],"study_design_scores_gemma":[0.0004642441,0.00006877106,0.0003283666,0.00009943495,0.000009620847,0.00002255943,0.00001499438,0.4846068,0.001935839,0.000002426916,0.5121593,0.000287657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01581498,0.0007408615,0.9316978,0.00116646,0.04984149,0.0002252598,0.00001035076,0.0004622568,0.0000404759],"genre_scores_gemma":[0.648535,0.00009962253,0.1010089,0.0004617987,0.2484035,0.0002099663,0.001074026,0.0001135952,0.00009353818],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8306889,"threshold_uncertainty_score":0.6247655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007959386259883986,"score_gpt":0.172547613062743,"score_spread":0.164588226802859,"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."}}