{"id":"W4393742370","doi":"10.5281/zenodo.2538118","title":"Supplementary Material: Comparing Formal Tools for System Design: a Case Study in the Railway Domain","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"Systems Engineering Methodologies and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission","keywords":"Domain (mathematical analysis); Computer science; Software engineering; Engineering; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002729287,0.00162121,0.001155833,0.007074077,0.001078793,0.003053404,0.002903849,0.002767938,0.2061699],"category_scores_gemma":[0.02625131,0.0007830022,0.001647902,0.00896682,0.0004345385,0.00221132,0.002284495,0.001814331,0.09894325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003019425,"about_ca_system_score_gemma":0.003020484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0262331,"about_ca_topic_score_gemma":0.05750453,"domain_scores_codex":[0.9972903,0.0006986114,0.000521991,0.0004970179,0.0007665906,0.0002255835],"domain_scores_gemma":[0.9744743,0.01659264,0.001492944,0.002992721,0.003890604,0.0005567856],"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":[0.00009514095,0.00004729713,0.001065104,0.003751235,0.00005127141,0.00003409571,0.00007406448,0.0005631657,0.0001221385,0.001242003,0.9877144,0.005240091],"study_design_scores_gemma":[0.000335165,0.00002813141,0.005368084,0.001355761,0.00005328729,0.00006683348,0.0002061076,0.0004051292,0.0002212878,0.002236492,0.9896888,0.0000349255],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001081822,0.00007803993,0.0001583517,0.00006002195,0.0000147266,0.00002232587,0.9983041,0.0002563569,0.0009977876],"genre_scores_gemma":[0.0004719912,0.0000827716,0.0007481544,0.00006078224,0.000005383162,0.0002296522,0.9975388,0.0001169306,0.0007455439],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2061699,"threshold_uncertainty_score":0.6897072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2160695004157089,"score_gpt":0.3342809592751417,"score_spread":0.1182114588594327,"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."}}