{"id":"W4414035867","doi":"10.21683/1729-2646-2025-25-3-12-20","title":"Collecting and processing dependability-related information in car building companies","year":2025,"lang":"en","type":"article","venue":"Dependability","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"PROTO Manufacturing (Canada)","funders":"","keywords":"Dependability; Computer science; Business; Software engineering","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006943993,0.0001667341,0.0004825322,0.001028512,0.0004696752,0.0004494753,0.0003938286,0.0001425557,0.00007626147],"category_scores_gemma":[0.008734846,0.0001352946,0.0001071471,0.004351204,0.0001860731,0.001392999,0.0002336346,0.0003296444,0.00001729881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000142246,"about_ca_system_score_gemma":0.0001784314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007875869,"about_ca_topic_score_gemma":0.001808059,"domain_scores_codex":[0.9967466,0.0004656308,0.001330889,0.0005072061,0.0006603357,0.0002893581],"domain_scores_gemma":[0.9971435,0.001636649,0.0002595632,0.0004898971,0.0003954597,0.00007490887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007755278,0.00006153024,0.6725686,0.00005930129,0.00001900749,0.00000183337,0.002703465,0.004497932,0.000140364,0.0008115208,0.0001034738,0.3189555],"study_design_scores_gemma":[0.0007467482,0.00002317031,0.678048,0.00006351708,0.00003368992,0.000005839138,0.005668025,0.1573004,0.0005103926,0.1542265,0.003127671,0.000246009],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867488,0.0002470278,0.006924416,0.001306636,0.0001244728,0.0002860386,0.000008976606,0.00005991386,0.004293701],"genre_scores_gemma":[0.9980729,0.0000306776,0.001712944,0.00008577921,0.000006260506,0.00001152851,0.00000398694,0.000003270627,0.00007267832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3187094,"threshold_uncertainty_score":0.999615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03456519788353967,"score_gpt":0.3648251808572924,"score_spread":0.3302599829737527,"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."}}