{"id":"W4361801143","doi":"10.21014/tc6-2022.014","title":"REPRESENTING METROLOGICAL TRACEABILITY IN DIGITAL SYSTEMS","year":2022,"lang":"en","type":"article","venue":"","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"New Zealand Government","keywords":"Traceability; Metrology; Context (archaeology); Computer science; Key (lock); Identification (biology); Systems engineering; Measurement uncertainty; System of measurement; Data science; Data mining; Software engineering; Engineering; Computer security; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.001079414,0.00006870291,0.0001429453,0.0001283826,0.0001261022,0.00008060506,0.0007218194,0.00004164687,0.00002467932],"category_scores_gemma":[0.0001834149,0.0000596233,0.000042562,0.0004967785,0.00002622209,0.0002615867,0.0001732047,0.0002366049,0.00001522216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008798166,"about_ca_system_score_gemma":0.00001450656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005755394,"about_ca_topic_score_gemma":0.000003619713,"domain_scores_codex":[0.998695,0.0001211635,0.000258062,0.0003867607,0.000308972,0.0002300771],"domain_scores_gemma":[0.9992816,0.00009629108,0.00005554976,0.0005181251,0.00002037998,0.00002804141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001752876,0.0005520518,0.752444,0.0000200941,0.00002541679,0.0001669006,0.0003728282,0.003331643,0.00360615,0.2327454,0.001631661,0.005086377],"study_design_scores_gemma":[0.004357875,0.001235782,0.2025926,0.00003139007,0.00001455031,0.001357343,0.008855523,0.6905615,0.00530509,0.02882405,0.05504059,0.001823742],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9438699,0.000202908,0.0340912,0.0008529145,0.0007405513,0.0003611193,0.000001489815,0.001002935,0.01887691],"genre_scores_gemma":[0.9989932,2.462919e-7,0.0003627615,0.00004524014,0.00001263576,0.00006903156,6.268544e-7,0.000002321748,0.0005139262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6872298,"threshold_uncertainty_score":0.2431368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03819052138488099,"score_gpt":0.2422921051311581,"score_spread":0.2041015837462772,"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."}}