{"id":"W4301436021","doi":"10.1007/978-3-031-01656-1_5","title":"Experimental Set Up and Datasets","year":2013,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on biomedical engineering","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Set (abstract data type); Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00592625,0.003676175,0.002203318,0.003566962,0.002481905,0.002468192,0.004060543,0.002151844,0.06167969],"category_scores_gemma":[0.01481947,0.001178647,0.002694953,0.003832258,0.001964244,0.00137766,0.002833514,0.0025174,0.05296294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009117668,"about_ca_system_score_gemma":0.003244654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002512428,"about_ca_topic_score_gemma":0.003921754,"domain_scores_codex":[0.9946436,0.001154965,0.0007678836,0.001691771,0.001295479,0.0004463293],"domain_scores_gemma":[0.9928305,0.001681899,0.0003531341,0.003150288,0.001604047,0.0003801859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006378981,0.003626532,0.01642706,0.009090688,0.001034374,0.0009946832,0.000402565,0.01836268,0.06448293,0.00865953,0.635035,0.235505],"study_design_scores_gemma":[0.002631591,0.003381921,0.03205615,0.001302432,0.00168424,0.001533185,0.0006917425,0.008840972,0.06501896,0.02534263,0.8569496,0.0005667048],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03291712,0.003120548,0.0577765,0.0009394692,0.001235888,0.0108335,0.8602211,0.01012493,0.02283099],"genre_scores_gemma":[0.01766833,0.0009513172,0.05474288,0.0008450473,0.0001922348,0.02581993,0.8912258,0.001268468,0.007286062],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06167969,"threshold_uncertainty_score":0.2063391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06520415369410412,"score_gpt":0.3178019001032091,"score_spread":0.252597746409105,"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."}}